JP2006191268A - Image output device outputting image while performing image processing a plurality of pixels at a time - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technique for speedily outputting an image of high picture quality. <P>SOLUTION: When image data are received from a digital camera, a pixel group gradation value is determined for each pixel group comprising a plurality of pixels and compared with thresholds stored for each pixel group to make a pixel group gradation value multi-valued, and obtained multi-valued result values are converted into dot data. Data of the image are received from a computer in the form of multi-valued result values for each of the pixel groups, and the multi-valued result values are converted into dot data by referring to correspondence relation where the multi-valued result values and presence/absence of dots formed in the pixel groups are related for each of the pixel groups. Consequently, even equipment having insufficient processing capability or memory is capable of receiving and converting image data from the digital camera into dot data and outputting an image. Further, even when data of high resolution are received from the computer, an image of high picture quality can be outputted. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

The present invention relates to a technique for outputting an image based on image data, and more particularly to a technique for outputting an image by performing predetermined image processing on the image data to generate dots with an appropriate density.

Image output devices that output images by forming dots on various output media such as print media and liquid crystal screens are widely used as output devices for various image devices. In these image output devices, images are handled in a state of being subdivided into small areas called pixels, and dots are formed in these pixels. Of course, if you look at each pixel, you can take only one of the states of whether or not dots are formed, but if you look at an area with a certain size, the density of dots to be formed will be coarse and dense. It is possible to output a multi-tone image by changing the dot formation density. Accordingly, if the dot formation density is appropriately controlled, a multi-tone image can be output. In this way, data for controlling dot formation so as to obtain an appropriate formation density is generated by performing predetermined image processing on an image to be output.

In recent years, these image output devices have been required to improve the image quality of output images. In order to meet these requirements, an image is divided into finer pixels (that is, a higher image quality). It has become increasingly handled as a resolution image. However, when the resolution of an image is increased, the time required for image processing increases as the number of pixels increases, making it difficult to output the image quickly. Therefore, a technique that enables image processing to be executed quickly has been proposed (Patent Document 1).

On the other hand, recently, there has been a strong demand for easily outputting images taken with a digital camera or the like. To meet these demands, a technology that connects the device that captured the image to the image output device, supplies the image data directly to the image output device, performs image processing in the image output device, and outputs the image is adopted. It has come to be. In addition, various improvements have been made on this technique, such as a technique for easily designating image data to be supplied to the image output apparatus (Patent Document 2, etc.).

JP 2002-185789 A JP-A-10-126724

However, since there is often a contradiction between the demand for higher image quality and the desire to output images easily, conventional image output devices have sufficient consideration for the configuration to satisfy both requirements. Was not paid. That is, when trying to output a high-quality image, the resolution of the image increases and the number of pixels increases, so that a large storage capacity is required for image processing. Further, coupled with the trend toward advanced image processing, it is premised that a certain degree of image processing should be performed using a computer or the like for a request for higher image quality. In such a case, it is important to process large image data quickly by utilizing a high processing capacity and a large storage capacity of a computer or the like. On the other hand, in order to meet the demand for easily outputting images, image data is directly supplied from an image capturing device such as a digital camera to the image output device without using an image processing device such as a computer. Thus, it is assumed that an image is output after image processing is performed in the image output apparatus. Accordingly, it is important to output an image while maintaining the image quality as much as possible within the limitation of the limited storage capacity and processing capability of the image output apparatus. As described above, the performance required for the image output apparatus greatly differs with respect to the two requirements, and thus sufficient consideration has not been given to the configuration for satisfying both.

The present invention has been made to solve the above-described problems in the prior art,
It is an object of the present invention to provide an image processing technique having a rational configuration capable of satisfying both a request for outputting a high-quality image and a request for outputting an image easily.

In order to solve at least a part of the problems described above, the image output apparatus of the present invention employs the following configuration. That is,
An image output device that outputs an image by forming dots based on dot data representing the presence or absence of dot formation for each pixel,
A first data converter that receives image data in which gradation values for each pixel are defined, and converts the image data into the dot data;
For each pixel group in which a predetermined number of pixels are collected, a multi-value quantization result value of a pixel group tone value that is a tone value representing the pixel group is received, and the multi-value quantization result value is received as the dot data A second data converter for converting into
Dot forming means for forming dots based on the dot data generated by either the first data converter or the second data converter;
The first data converter is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor Multi-value conversion means for multi-value the pixel group gradation value by comparing the tone value;
Multi-value conversion that converts the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group A conversion unit including a result value conversion unit,
The second data converter is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is that the conversion unit includes dot data generation means for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data.

The image output method of the present invention corresponding to the image output system described above is
An image output method for outputting an image by forming dots based on dot data representing the presence or absence of dot formation for each pixel,
When receiving image data in which a gradation value for each pixel is defined, the step (1) of converting the image data into the dot data;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is Converting to the dot data (2);
And (3) forming a dot based on the dot data generated by either the step (1) or the step (2),
The step (1)
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-step (1-a) for converting the pixel group gradation value into a multi-value by comparing the tone value;
A sub-step of converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( 1-b) and
The step (2)
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is a process including a sub-process (2-a) for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data.

In such an image output apparatus and image output method of the present invention, an image to be output in either form of image data in which a gradation value for each pixel is defined or a multi-value quantization result value for each pixel group. Receive data about. In either case, the received data is converted into dot data by each method, and then an image is output by forming dots based on the obtained dot data. Here, when the data about the image to be output is received in the form of image data, after determining the pixel group gradation value from the gradation value of each pixel grouped in the pixel group, for each pixel group By comparing at least one stored threshold value and the pixel group tone value, the pixel group tone value is converted into a multi-value quantization result value. Next, the multi-value quantization result value is converted into dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group. on the other hand,
When data about an image to be output is received in the form of a multi-value quantization result value for each pixel group, the multi-value quantization result value is stored in the pixel group by referring to the correspondence stored in advance. Dot data is generated by determining the presence or absence of dot formation for each pixel. In correspondence,
Since the multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are associated with each pixel group, referring to this correspondence, each multi-value quantization result value The presence or absence of dot formation for a pixel can be determined. As described above, an image is output based on dot data generated by one of the methods in accordance with the form in which data about the image to be output is received.

Although details will be described later, if a multi-value quantization result value is generated from image data using the above-described method, and dot data is generated from the obtained multi-value quantization result value, usable storage capacity and Even when the processing capability is limited, an image can be output while maintaining sufficient image quality and processing speed. Note that the image data in which the gradation value for each pixel is defined may be data that can determine the gradation value for each pixel, and is not necessarily data in which the gradation value is set for each pixel. There is no. For example, the gradation value set for each pixel is described in a compressed state for a predetermined number of pixels such as so-called JPEG, and the gradation value for each pixel is obtained by decompressing this data. It does not matter if the data is such that

On the other hand, when data is received from an image processing apparatus such as a computer, that is, when data is received in a form that has undergone some image processing, it is received in the form of a multi-value quantization result value for each pixel group and stored in advance. The multi-value quantization result value is converted into dot data while referring to the corresponding relationship. Compared to data representing the presence or absence of dot formation for all pixels in the image, the multi-value quantization result value for each pixel group can be much smaller data, so an image with high resolution and therefore a large number of pixels is output. Even if you can receive data quickly. Further, by referring to the correspondence relationship, the multi-value quantization result value can be quickly converted into dot data, so that an image can be output quickly. In addition, the reason will be described in detail later, but if the correspondence is set appropriately, the image quality will not deteriorate even when the image is output in this way.

Further, when generating dot data by receiving image data, it may be generated as follows. That is, a conversion table in which number data representing the number of dots formed in a pixel group and a multi-value quantization result value are associated with each pixel group is stored in advance, and the pixel is obtained by referring to the conversion table. Number data is generated from the multi-value quantization result values obtained for each group. Here, the number data need only be data that can specify the number of dots formed in the pixel group, and need not be data that directly represents the number of dots. The number data and the multi-value quantization result value are associated with each pixel group as long as the number data and the pixel group are specified as long as the corresponding multi-value quantization result value can be determined. Or may be associated in a functional expression or the like. In addition to such a conversion table, the order in which dots are formed for each pixel in the pixel group is also stored for each pixel group. Then, based on the number data for each pixel group obtained by referring to the conversion table and the order stored for each pixel in the pixel group, the dot formation presence / absence is determined for each pixel. Data may be generated.

Although the detailed reason will be described later, the order in which dots are formed in the pixel group is appropriately stored for each pixel group, and the dot for each pixel is determined based on the number data and the stored appropriate order. If the presence / absence of formation is determined, it is possible to appropriately determine the presence / absence of dot formation and output a high-quality image.

In addition, when determining whether or not to form dots for each pixel in the pixel group from the number data, it may be determined as follows. That is, first, the number data is converted into intermediate data. Here, the intermediate data means that a dot is formed when the number of pixels included in the pixel group is N and the number of dots formed in the pixel group is M.
This is data consisting of continuous data and (N−M) continuous data which means that dots are not formed. Next, by reading the data at the position corresponding to the order stored in each pixel in the pixel group from the intermediate data obtained for each pixel group by converting the number data, each pixel in the pixel group It may be possible to determine whether or not to form dots.

Once the number data is converted into intermediate data in this way, the presence or absence of dot formation for each pixel can be determined easily and quickly simply by reading the data at the corresponding position from the intermediate data. It becomes possible.

Alternatively, it is also possible to obtain intermediate data immediately from the multi-value quantization result value, instead of obtaining the intermediate data after converting the multi-value quantization result value into number data. That is, the multi-value quantization result value and the intermediate data may be stored in association with each pixel group, and the intermediate data may be obtained immediately from the multi-value quantization result value.

In this way, since intermediate data can be obtained immediately without generating the number data, it is possible to quickly determine the presence or absence of dot formation for each pixel and, in turn, to output an image quickly. It becomes possible.

Alternatively, in the image output device described above, after receiving the image data and converting the pixel group gradation value for each pixel group into a multi-value quantization result value, the multi-value quantization result value and the dot for each pixel in the pixel group The multi-value quantization result value may be converted into dot data by referring to the correspondence relationship associated with the presence or absence of formation.

By doing this, the multi-value quantization result value for each pixel group received as image data is converted into dot data, and the multi-value quantization result value determined for each pixel group from the image data is converted to dot data. Since it can also be used when converting to data, it is possible to save the storage capacity of the image output apparatus, which is preferable.

Further, in such an image output apparatus, the pixel group is classified into a plurality of types according to the position in the image, a classification number is assigned to each pixel group, and the pixel group is identified using the classification number. However, dot data may be generated. That is, when converting the pixel group gradation value to the multi-value quantization result value, the pixel group gradation value is multi-valued by comparing with at least one threshold value stored for each classification number. Further, the multi-value quantization result value is converted into dot data based on the obtained multi-value quantization result value and the classification number for the pixel group from which the multi-value quantization result value is obtained. Alternatively, the multi-value quantization result value and the presence / absence of dot formation for each pixel in the pixel group are stored in correspondence in association with each classification number, and the multi-value quantization result value is referenced with reference to the correspondence relationship. It is good also as producing | generating dot data from.

Thus, if the pixel group is identified based on the classification number assigned according to the position in the image, even if the same pixel group gradation value continues across a plurality of pixel groups, these pixels Since the group classification numbers are different, the same multi-value quantization result value does not continue over a plurality of pixel groups. For this reason, dots are formed in a constant pattern, and there is no possibility that the image quality deteriorates. Also, for subsequent conversions, if conversion is performed while identifying pixel groups using classification numbers, conversion can be performed appropriately according to the position in the image, so a high-quality image can be output. Is possible.

In addition, when classifying a pixel group according to the position in an image, it is good also as classifying into at least 100 types or more of pixel groups.

For example, if the pixel group is classified into only a few types, when the same pixel group gradation value continues over a wide area, the multi-value quantization result value may be repeated in a certain pattern, It may happen that a certain regularity appears in the generation pattern. In order to avoid this, it is desirable to classify the pixel group into a larger number of types.
If the pixel groups are classified into 00 types or more, it is possible to suppress the occurrence of a certain pattern in the generation of dots to such an extent that a practical problem does not occur.

Alternatively, in such an image output apparatus, the multiplication value of the number of types for classifying the pixel group and the number of pixels collected in the pixel group may be set to be at least 1000 or more.

If the number of pixels included in a pixel group increases, a large number of dot generation patterns can be obtained within one pixel group. Therefore, even when the number of types for classifying the pixel group is not large enough, if the number of pixels included in the pixel group is large, this is compensated to prevent a certain regularity from appearing in the dot generation pattern. be able to. According to experience, if the product of the number of types that classify a pixel group and the number of pixels included in the pixel group is selected to be 1000 or more, the occurrence of a certain pattern in the generation of dots is suppressed. Thus, it is possible to avoid the occurrence of practical problems.

Further, in such an image output device, a plurality of types of dots having different gradation values that can be expressed per single dot can be formed, and the multilevel halftoning result value received for each image data or pixel group is converted into a plurality of types of dots. After conversion into dot data representing the presence or absence of formation, various dots may be formed based on the obtained dot data.

When multiple types of dots can be formed, the time required to generate the dot data from the image data tends to increase, or the time required to supply the generated dot data to the image output device tends to increase. is there. In contrast, the image output apparatus of the present invention can convert image data into dot data with a simple process even if the number of dots that can be formed increases. Alternatively, if image data is received in the form of a multi-value quantization result value for each pixel group, the data can be quickly received even when there are many types of dots. Eventually, even when receiving image data with a specified gradation value for each pixel or when receiving multi-value quantization result values for each pixel group, it is possible to generate dot data quickly and output an image quickly. Therefore, it is preferable.

Further, if attention is paid to the fact that dot data is generated by performing image processing by an appropriate method between when image data is received and when a multi-value quantization result value for each pixel group is received, the present invention Can be grasped as an image processing apparatus or an image processing method. That is, the image processing apparatus of the present invention is
An image processing apparatus that generates dot data representing the presence or absence of dot formation for each pixel by applying predetermined image processing to data representing an image, and supplies the dot data to an image output apparatus,
A first data converter that receives image data in which gradation values for each pixel are defined, and converts the image data into the dot data;
For each pixel group in which a predetermined number of pixels are collected, a multi-value quantization result value of a pixel group tone value that is a tone value representing the pixel group is received, and the multi-value quantization result value is received as the dot data A second data converter for converting into
Dot data supply means for supplying the dot data generated by either the first data conversion unit or the second data conversion unit to the image output device,
The first data converter is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor Multi-value conversion means for multi-value the pixel group gradation value by comparing the tone value;
Multi-value conversion that converts the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group A conversion unit including a result value conversion unit,
The second data converter is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is that the conversion unit includes dot data generation means for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data.

Further, the image processing method of the present invention corresponding to the above image processing apparatus is as follows.
An image processing method for generating dot data representing the presence / absence of dot formation for each pixel by applying predetermined image processing to data representing an image and supplying the dot data to an image output device,
When receiving image data in which a gradation value for each pixel is defined, the step (A) of converting the image data into the dot data;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A step (B) of converting into the dot data;
And (C) supplying the dot data generated by either the step (A) or the step (B) to the image output device,
The step (A)
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-process (Aa) that multi-values the pixel group gradation value by comparing the tone value;
A sub-step of converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( A-b) and
The step (B)
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is a process including a sub-process (Ba) for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data.

Also in the image processing apparatus and the image processing method of the present invention, when image data is received in either form of image data in which a gradation value for each pixel is defined or a multi-value quantization result value for each pixel group. Depending on the received form, it is converted into dot data by each method.

In this way, when image data is received, dot data can be generated while maintaining sufficient image quality and processing speed even when the usable storage capacity and processing capability are limited. Further, when receiving a multi-value quantization result value for each pixel group, it is possible to quickly receive data even if it is high resolution data, and to quickly generate dot data.

Furthermore, the present invention can also be realized using a computer by causing a computer to read a program for realizing the above-described image output method or image processing method. Therefore, the present invention includes the following program or a mode as a recording medium on which the program is recorded. That is, the program of the present invention corresponding to the image output method described above is
A program for realizing a method of outputting an image by forming a dot on the basis of dot data representing the presence or absence of dot formation for each pixel by a computer,
A function (1) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A function (2) for converting to the dot data;
A function (3) for forming dots based on the dot data generated by either the function (1) or the function (2) is realized using a computer,
The function (1) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (1-a) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence / absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( 1-b) and
The function (2) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is a function having a sub-function (2-a) for generating dot data by determining the presence / absence of dot formation for each pixel in the pixel group from the value.

The recording medium of the present invention corresponding to the above program is
A recording medium on which a program for outputting an image is recorded so as to be readable by a computer by forming dots based on dot data representing the presence or absence of dot formation for each pixel,
A function (1) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A function (2) for converting to the dot data;
A program that uses a computer to store a function (3) that forms dots based on the dot data generated by either the function (1) or the function (2);
The function (1) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (1-a) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence / absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( 1-b) and
The function (2) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. A program having a sub-function (2-a) for generating dot data by determining whether or not to form dots for each pixel in the pixel group from the values.

Furthermore, the program of the present invention corresponding to the above-described image processing method is as follows:
A computer program for realizing a method of generating dot data representing the presence / absence of dot formation for each pixel and supplying it to an image output device by performing predetermined image processing on the data representing the image. And
A function (A) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A function (B) for converting to the dot data;
The function (C) for supplying the dot data generated by either the function (A) or the function (B) to the image output device is realized using a computer.
The function (A) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (Aa) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence / absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( A-b) and
The function (B) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is a function having a sub-function (Ba) for generating dot data by determining whether or not to form dots for each pixel in the pixel group from the values.

The recording medium of the present invention corresponding to the above program is
A recording medium on which a computer-readable program for generating dot data representing the presence / absence of dot formation for each pixel and supplying it to an image output device by performing predetermined image processing on data representing an image Because
A function (A) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A function (B) for converting to the dot data;
A program for realizing, using a computer, a function (C) for supplying the dot data generated by either the function (A) or the function (B) to the image output device;
The function (A) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (Aa) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence / absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( A-b) and
The function (B) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. The gist of the present invention is a function having a sub-function (Ba) for generating dot data by determining whether or not to form dots for each pixel in the pixel group from the values.

If such a program or a program recorded on a recording medium is read into a computer and the various functions described above are realized using the computer, dot data can be generated quickly and extended while maintaining sufficient image quality. Therefore, it is possible to output an image quickly.

In the following, in order to more clearly explain the operation and effect of the present invention, the embodiment of the present invention will be described.
The description will be given in the following order.
A. Summary of Examples:
B. Device configuration:
C. Overview of image printing process:
D. First dot data generation process:
D-1. Process overview:
D-2. Pixel group classification number:
D-3. Setting method of threshold table:
D-4. How to set the conversion table:
D-5. To set the order value matrix:
D-6. Reasons for printing high-quality images:
E. Second dot data generation process:
E-1. Process overview:
E-2. Reasons why multi-value quantization result values can be converted to code data:
E-3. How to quickly obtain multi-valued result values in a computer:
F. Variations:

A. Summary of Examples:
Prior to detailed description of the embodiment, an outline of the embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an overview of a printer 10 as an image output apparatus of the present embodiment. As shown in the figure, the printer 10 of this embodiment is mainly composed of a first data conversion unit, a second data conversion unit, a dot formation module, and the like. The dot formation module receives dot data representing the presence or absence of dot formation for each pixel, and outputs an image by forming dots on the print medium. The dot data is generated by either the first data conversion unit or the second data conversion unit and supplied to the dot formation module.

The printer 10 can receive image data from a photographing device such as the digital camera 20 and output an image, or can receive data processed by the computer 30 and output the image. In a normal printer, when data subjected to image processing by a computer or the like is received, data converted into dot data is received. However, in the printer 10 of this embodiment, as described below, dot data is received. The data is received in a different form.

Image data from the digital camera 20 or the like is supplied to the first data converter and converted to dot data as follows. First, the pixel group tone value determination module converts the image data into pixel group tone values. Here, the pixel group gradation value is a gradation value representing a pixel group in a pixel group in which a predetermined number of pixels are collected. Next, the pixel group gradation value is converted into a multi-value quantization result value by comparing the pixel group gradation value with the threshold value while referring to a threshold value table in which at least one threshold value is stored for each pixel group. The multi-value quantization result value thus obtained for each pixel group is converted into dot data and supplied to the dot formation module.

On the other hand, when receiving data subjected to image processing by the computer 30 or the like,
In the printer 10 of this embodiment, it is received in the form of a multi-value quantization result value for each pixel group. That is, image data representing an image to be printed is converted into a multi-value quantization result value for each pixel group by a multi-value quantization result value generation module realized using a function of the computer 30 or the like, and the obtained multi-value is obtained. The value conversion result value is supplied to the printer 10. If image data generated inside the computer 30 or image data photographed by a photographing device such as the digital camera 20 is supplied to the multi-value quantization result value generation module, these image data are converted into multi-value quantization results for each pixel group. Can be converted to a value. The multi-value quantization result value generated in this way is supplied to the second data conversion unit of the printer 10. The second data conversion unit stores a conversion table in which the multi-value quantization result value and the presence / absence of dot formation for each pixel in the pixel group are associated with each pixel group. By referencing, the multi-value quantization result value is converted into dot data and supplied to the dot formation module.

As described above, when image data is directly received from the digital camera 20 or the like, the image data is once converted into a pixel group gradation value and converted into a multi-value quantization result value by referring to a threshold value table. Dot data is generated from the obtained multi-value quantization result value. Although the detailed reason will be described later, in this way, the image data can be converted into dot data without squeezing the memory mounted in the printer 10. Therefore, it is not necessary to reduce the resolution or simplify the image processing in order to save memory, and an image can be printed while maintaining high image quality. On the other hand, when image-processed data can be received by the computer 30 or the like, it is received in the form of a multi-value quantization result value for each pixel group, and the multi-value quantization result value is converted into dot data while referring to the conversion table. . Rather than dot data representing the presence or absence of dot formation for each pixel,
Since the multi-value quantization result value for each pixel group has a smaller data amount, data can be received quickly even in a high-resolution image with a large number of pixels by receiving data in the form of multi-value quantization result values. Can receive. In addition, by referring to the conversion table, the multi-value quantization result value can be quickly converted into dot data, so even a high-resolution image can be printed quickly. Eventually, when receiving data that has been subjected to image processing by the computer 30 or the like, even a high-resolution image can be quickly output with high image quality.
Even when image data is directly received from 0 or the like, it is possible to output an image while maintaining sufficient image quality. Hereinafter, such an embodiment will be described in detail.

B. Device configuration :
FIG. 2 is an explanatory diagram illustrating the configuration of the computer 100 that supplies the multi-value quantization result value for each pixel group to the color printer 200 of this embodiment. The computer 100 is a well-known computer configured by connecting a ROM 104, a RAM 106, and the like with a bus 116 around a CPU 102.

The computer 100 includes a disk controller DDC 109 for reading data such as the flexible disk 124 and the compact disk 126, a peripheral device interface PIF 108 for exchanging data with peripheral devices, a video interface VIF 112 for driving the CRT 114, and the like. It is connected. A color printer 200, a hard disk 118, and the like, which will be described later, are connected to the PIF 108. If the digital camera 120, the color scanner 122, etc. are connected to the PIF 108, the digital camera 12
It is also possible to perform image processing on an image captured by 0 or the color scanner 122.
If the network interface card NIC 110 is installed, the computer 1
00 can be connected to the communication line 300 to obtain data stored in the storage device 310 connected to the communication line.

FIG. 3 is an explanatory diagram showing a schematic configuration of the color printer 200 of the present embodiment. The color printer 200 is an ink jet printer capable of forming dots of four color inks of cyan, magenta, yellow, and black. Of course, in addition to these four color inks, a total of six ink dots can be formed, including cyan (light cyan) ink with low dye or pigment concentration and magenta (light magenta) ink with low dye or pigment concentration. An ink jet printer can also be used. In the following, depending on the case, cyan ink, magenta ink, yellow ink, black ink, light cyan ink, and light magenta ink may be changed to C ink,
It may be abbreviated as M ink, Y ink, K ink, LC ink, and LM ink.

As shown in the figure, the color printer 200 drives a print head 241 mounted on a carriage 240 to eject ink and form dots, and the carriage 240 is reciprocated in the axial direction of a platen 236 by a carriage motor 230. A mechanism for transporting the printing paper P by the paper feed motor 235, a control circuit 260 for controlling dot formation, carriage 240 movement, and printing paper transportation.

The carriage 240 includes an ink cartridge 242 that stores K ink, C ink,
An ink cartridge 243 that stores various inks of M ink and Y ink is mounted. When the ink cartridges 242 and 243 are mounted on the carriage 240, each ink in the cartridge is supplied to ink discharge heads 244 to 247 for each color provided on the lower surface of the print head 241 through an introduction pipe (not shown).

FIG. 4 is an explanatory diagram showing the arrangement of the ink jet nozzles Nz in the ink ejection heads 244 to 247. As shown in the figure, the bottom surface of the ink ejection head has C, M, Y
, K are ejected, and four sets of nozzle rows are formed, and 48 nozzles Nz are arranged at a constant nozzle pitch k per set of nozzle rows.

The control circuit 260 is a CPU, ROM, RAM, PIF (peripheral device interface)
Etc. are connected to each other via a bus. The control circuit 260 is connected to the carriage motor 23.
The main scanning operation and the sub scanning operation of the carriage 240 are controlled by controlling the operation of 0 and the paper feed motor 235. The multi-value quantization result value data output from the computer 100 or the image data output from the digital camera 120 or the like is temporarily supplied to the control circuit 260, and predetermined processing described later is performed in the control circuit 260. And converted to dot data. Then, ink droplets are ejected from each nozzle by driving the ink ejection heads 244 to 247 according to the dot data in accordance with the movement of the carriage 240 in the main scanning and the sub scanning. Thus, the color printer 200 can print a color image by forming ink dots of respective colors at appropriate positions on the print medium under the control of the control circuit 260.

Further, the color printer 200 of the present embodiment can control the size of the ink dots by controlling the size of the ink droplets to be ejected. Hereinafter, the color printer 20
A method for forming ink dots having different sizes of 0 will be described.
First, the internal structure of the nozzle that discharges each color ink will be described.

FIG. 5A is an explanatory diagram showing the internal structure of a nozzle that ejects ink. Each of the ink discharge heads 244 to 247 for each color is provided with a plurality of such nozzles. As shown in the figure, each nozzle is provided with an ink passage 255, an ink chamber 256, and a piezo element PE on the ink chamber. Ink cartridges 242 and 243 on the carriage 240
Is attached, the ink in the cartridge passes through the ink gallery 257 and the ink chamber 25.
6 is supplied. The piezo element PE is an element that performs electro-mechanical energy conversion at an extremely high speed because the crystal structure is distorted when a voltage is applied as is well known. In this embodiment, the piezo element PE
The side wall of the ink chamber 256 is deformed by applying a voltage having a predetermined waveform between the electrodes provided at both ends of the ink chamber 256. As a result, the volume of the ink chamber 256 is reduced, and ink corresponding to the reduced volume is ejected from the nozzle Nz as ink droplets Ip. This ink droplet Ip is the platen 236.
Ink dots are formed on the printing paper by soaking into the printing paper P mounted on the printing paper.

FIG. 5B is an explanatory diagram showing the principle of changing the size of the ink droplets ejected by controlling the voltage waveform applied to the piezo element PE. In order to eject the ink droplet Ip from the nozzle, a pre-voltage is applied to the piezo element PE and the ink chamber 256 is supplied from the ink gallery 257.
The ink is once sucked in, and then a positive voltage is applied to the piezo element PE to reduce the ink chamber volume, thereby ejecting the ink droplet Ip. Here, if the ink suction speed is appropriate, ink corresponding to the amount of change in the ink chamber volume is sucked, but if the suction speed is too fast, there is a passage resistance between the ink gallery 257 and the ink chamber 256. Therefore, the inflow of ink from the ink gallery 257 is not in time. As a result, the ink in the ink passage 255 flows back into the ink chamber, and the ink interface near the nozzle is largely retracted. A voltage waveform a shown in FIG. 5B in practice shows a waveform for sucking ink at an appropriate speed, and a voltage waveform b shown by a broken line.
Shows an example of a waveform of suction at a speed larger than the appropriate speed.

When a positive voltage is applied to the piezo element PE in a state where sufficient ink is supplied into the ink chamber 256, an ink droplet Ip having a volume corresponding to the volume reduction of the ink chamber 256 is ejected from the nozzle Nz. On the other hand, when a positive voltage is applied in a state where the ink supply amount is insufficient and the ink interface is largely retracted, the ejected ink droplet becomes a small ink droplet. As described above, in the printer 200 of the present embodiment, the size of the ink droplet to be ejected is controlled by changing the suction speed of the ink by controlling the voltage waveform applied before the ink droplet is ejected. It is possible to form three types of ink dots: dots, medium dots, and small dots.

Of course, not only three types but also more types of dots can be formed. Further, the size of the ink dots formed on the printing paper may be controlled by using a method in which a plurality of fine ink droplets are ejected at a time and the number of ejected ink droplets is controlled. By controlling the size of the ink dots in this way, it is possible to print a higher quality image by using different ink dots depending on the area of the image to be printed. .

Note that various methods can be applied to the method of ejecting ink droplets from the ink ejection heads of the respective colors. That is, a method of ejecting ink droplets using a piezoelectric element, a method of ejecting ink droplets by generating bubbles in the ink passage with a heater arranged in the ink passage, and the like can be used. In addition, instead of ejecting ink droplets, there is a printer that uses a phenomenon such as thermal transfer to form ink dots on printing paper, or a method that uses static electricity to attach toner powder of each color onto the print medium. It is also possible to use it.

The color printer 200 having the above hardware configuration includes a carriage motor 2.
30 is driven to move the ink ejection heads 244 to 247 of each color in the main scanning direction with respect to the printing paper P, and the paper feeding motor 235 is driven to move the printing paper P in the sub-scanning direction. Let The control circuit 260 drives the nozzles at an appropriate timing to eject ink droplets in synchronization with the main scanning and sub-scanning movements of the carriage 240, whereby the color printer 200 prints a color image on the printing paper. be able to.

As described above, the color printer 200 according to this embodiment can receive image data from the digital camera 120 or the like and immediately print an image.
It is also possible to receive data that has undergone image processing at 0 or the like and print an image. Here, as described above, the CPU, RA are included in the control circuit 260 of the color printer 200.
Since M, ROM, etc. are mounted, it is possible in principle to carry out the processing performed by the computer 100 in the color printer 200. However, since the processing capability of the color printer 200 is not as high as that of the computer 100 and the amount of memory that can be used is limited, it is actually difficult to execute the image processing performed in the computer 100 as it is. It is. Therefore, in the color printer 200 according to the present embodiment, the image processing method is switched appropriately between the case where the image data to be printed is received from the computer 100 and the case where the image data is received from the digital camera 120 or the like as follows. It is possible to print an image. Hereinafter, a process of printing an image in the color printer 200 of the present embodiment will be described.

C. Overview of image printing process:
FIG. 6 is a flowchart showing the flow of image printing processing performed by the color printer 200 of this embodiment for printing an image. Such processing is executed by the function of the CPU built in the control circuit 260 of the color printer 200 when data about an image to be printed is received from an image processing apparatus such as the computer 100 or a photographing device such as the digital camera 120. Process. Hereinafter, the computer 100 will be described as a representative example of an image processing apparatus, and the digital camera 120 will be described as a representative example of a device that outputs image data without performing image processing, such as a photographing device. That is, “computer 100 in the following description.
"" Refers to various image processing apparatuses typified by computers, and "digital camera 120" refers to image data such as various photographic devices typified by digital cameras. It shall be the device that outputs as it is. In the following description, the color printer 200 is described as receiving data directly from the computer 100 or the digital camera 120, but of course, the data may be received via a recording medium.

When the image printing process is started, the CPU of the control circuit 260 first starts with the computer 10.
0 or image data is read from the digital camera 120 (step S100).
). The color printer 200 of this embodiment receives image data from the digital camera 120 in the form of data in which the gradation value for each pixel is defined, and from the computer 100 in the form of a multi-value quantization result value for each pixel group. Receive image data.

Next, it is determined whether the received image data is a multi-value quantization result value for each pixel group (step S102). Such determination can be made, for example, by setting information indicating whether the data is a multi-value quantization result value or gradation value data for each pixel in the data header and analyzing the header. If it is determined that the data is not multi-value quantization result value data for each pixel group (step S102: no), it is determined that the image data defines the gradation value for each pixel.
First dot data generation processing is performed (step S104). In the first dot data generation process, image data is converted into dot data as described later. On the other hand, when it is determined that the data is a multi-value quantization result value for each pixel group (step S102: yes), a second dot data generation process is performed (step S106). In the second dot data generation process, the multi-value quantization result value for each pixel group can be promptly converted into dot data by a method described later.

In this way, either the first dot data generation process or the second dot data generation process is performed on the received image data, and dots are formed based on the obtained dot data (step S108). ). That is, by ejecting ink droplets according to dot data in accordance with the main scanning and sub-scanning movements of the carriage 240, ink dots having an appropriate size are formed at appropriate positions on the printing paper. As described above, when all the dots are formed according to the dot data, the image has been printed, so the image printing process shown in FIG. 6 is terminated.

As described above, in the color printer 200 of this embodiment, when the image data to be printed is received in the form of image data in which the gradation value is defined for each pixel (step S10).
2: no), by performing the first dot data generation process, dot data is generated by the following method, and when image data is received in the form of a multi-value quantization result value for each pixel group (step S102) : Yes), the second dot data generation process is performed to generate dot data by the following method. Therefore, the image data received from the digital camera 120 can be printed while maintaining high image quality. In addition, when high-resolution image data is received from the computer 100, it is possible to quickly print a high-quality image. In the following, first, the outline of the first dot data generation process will be described, and then the reason why image data received from the digital camera 120 can be printed while maintaining high image quality by performing such process will be described. To do. Similarly for the second dot data generation process,
First, an overview of the processing will be described, and then the reason why a high-resolution image can be quickly printed with high image quality by performing such processing will be described.

D. First dot data generation process:
D-1. Process overview:
FIG. 7 is a flowchart showing the flow of the first dot data generation process. This process is a process executed by the CPU mounted on the control circuit 260 of the color printer 200 when image data is received from the digital camera 120 during the image printing process shown in FIG.

When the first dot data generation processing is started, first, resolution conversion processing is performed (step S200). The resolution conversion process is a process for converting the resolution of the image data supplied from the digital camera 120 to a resolution (printing resolution) at which the color printer 200 prints an image. When the resolution of the image data is lower than the print resolution, an interpolation operation is performed to generate new image data between the pixels. Conversely, when the resolution of the image data is higher than the print resolution, the data is at a certain rate. Is performed to match the resolution of the image data with the print resolution.

Next, the CPU mounted on the color printer 200 performs color conversion processing (step S).
202). The color conversion process is a process of converting the color system of image data received from the digital camera 120 into the color system adopted by the color printer 200. That is, in the digital camera 120, an RG that normally expresses a color by a combination of R, G, and B gradation values.
B color system is adopted, and the image data received from the digital camera 120 is RGB
Color image data. On the other hand, as described above, the color printer 200 uses the C, M
A CMY color system that expresses colors using four color inks of, Y, and K is employed. Therefore, color conversion processing is performed to convert the RGB color image data received from the digital camera 120 into data expressed by gradation values of each color of C, M, Y, and K. The color conversion process is performed by referring to a three-dimensional numerical table called a color conversion table (LUT). LU
In T, gradation values of C, M, Y, and K colors obtained by color conversion are stored in advance for RGB color image data. In the process of step S202, RGB color image data can be quickly color-converted into C, M, Y, and K image data by referring to this LUT.

By performing the color conversion process as described above, the image data of each color of RGB is converted into C, M,
Once converted into image data for each color Y and K, this time, the image data for each color is converted to dot data. In addition, since such processing is similarly performed for each color of C, M, Y, and K, in order to avoid complicated description, in the following description, when the color is not specified, C, M,
It means that the same processing is performed for each color of Y and K.

When converting image data into dot data, first, a predetermined number of pixels adjacent to each other are grouped to generate a pixel group (step S204). Here, 4 in the main scanning direction.
A total of eight pixels for two pixels in the sub-scanning direction are grouped into a pixel group. Note that the pixels to be grouped as a pixel group do not need to be pixels having vertical and horizontal positions aligned in a rectangular shape as described above. good.

Next, the pixel group gradation value and the pixel group classification number are determined (step S206). The pixel group tone value is a tone value that represents a pixel group, and can be easily obtained as follows. For example, an average value of image data assigned to each pixel in the pixel group can be obtained and used as a pixel group gradation value. Alternatively, image data assigned to the largest number of pixels in the pixel group, and further, image data of a pixel at a specific position in the pixel group can be used as the pixel group gradation value.

In addition, the pixel group classification number, simply speaking, when using the dither matrix to determine the presence or absence of dot formation for each pixel in the pixel group, which part of the dither matrix is applied to the pixel group. It is a number that represents. The pixel group classification number can be determined very simply as follows. FIG. 8 is an explanatory diagram showing a method of determining the pixel group classification number. FIG. 8A shows one pixel group generated by grouping eight pixels in an image. Hereinafter, a method for determining the classification number for this pixel group will be described. still,
A pixel group focused on for determining the classification number as shown in FIG. 8A is referred to as a focused pixel group.

Now, assuming that the upper left corner of the image is the origin, the pixel position is represented by the number of pixels from the origin in the main scanning direction and the sub-scanning direction. The position of the pixel group is represented by the pixel position of the pixel at the upper left corner of the pixel group. In FIG. 8A, the pixel indicating the position of the pixel group of interest is displayed with a black circle. Assume that the pixel position of this pixel is (X, Y). The classification number of the pixel group of interest can be determined very easily simply by displaying X and Y in binary and reading the data stored in the predetermined bits. For example, as shown in FIG.
Assume that X and Y representing the position of the pixel group of interest are 10-bit data, respectively. And X
The value obtained by reading the data from the 4th bit to the 8th bit of the most significant bit is N, and Y
Let M be the value obtained by reading the data from the 4th bit to the 8th bit of the most significant bit.
Then, in this example,
N + (M−1) × 32 (1)
By calculating, the pixel group classification number can be easily determined. The meaning of the pixel group classification number and the reason why the pixel group classification number can be determined in this manner will be described in detail later.

When the pixel group classification number and the pixel group gradation value are determined in this way, the pixel group gradation value is converted into a multi-value by referring to a threshold value table described below (step S208). FIG.
It is explanatory drawing which showed the threshold value table referred when multi-value-izing a pixel group gradation value. As shown in the figure, at least one threshold set is set for each classification number in the threshold table. This threshold value represents the pixel group gradation value at which the multi-value quantization result value is switched when the pixel group gradation value is increased from the gradation value 0 to the gradation value 255.

As an example, a pixel group with classification number 1 will be described. For the classification number 1, a set of threshold values including a plurality of threshold values from the threshold value “2” to the threshold value “243” is set. Since the smallest threshold among these is “2”, the pixel group gradation value less than this value, that is, the pixel group gradation value “0” or “1” is set to the multi-value quantization result value “0”. Multi-valued. Also, since the second smallest threshold in the threshold set is “15”, the pixel group gradation value is “2” or more and “
If the value is less than 15 ”, the value is converted to a multi-valued result value“ 1 ”. Similarly, the pixel group gradation value “1”
If it is 5 ”or more and less than“ 18 ”, it is multi-valued to the multi-value quantization result value“ 2 ”, and the pixel group gradation value“ 18 ”.
If it is less than “24” as described above, it is converted into a multi-value into the multi-value conversion result value “3”. In this way, by comparing the pixel group tone value of the pixel group with a set of threshold values set in the threshold table, the pixel group tone value is obtained by obtaining the number of threshold values smaller than the pixel group tone value. Can be converted into a multivalued result value.

As shown in FIG. 9, the threshold value set in the threshold value table has a different threshold value and the number of threshold values for each classification number. For this reason, even if the pixel group gradation value is the same value, it is multivalued to a different value depending on the pixel group classification number.

FIG. 10 is an explanatory diagram conceptually showing a state in which pixel group gradation values are converted into different multi-value quantization result values in accordance with pixel group classification numbers. In FIG. 10, the multi-value quantization result value for the pixel group tone value is displayed using a line graph in which the horizontal axis represents the pixel group tone value and the vertical axis represents the multi-value quantization result value. In the figure, the multi-value conversion result is shown for five pixel groups having different classification numbers N1 to N5. The origin position of the conversion result value is displayed while being shifted little by little in the vertical axis direction.

As an example, a pixel group with classification number N1 indicated by a thick solid line in the figure will be described. In the range where the pixel group gradation value is 0 to 4, the multi-value quantization result value is “0”. The gradation value is 5-2
In the range of 0, the multi-value quantization result value increases to “1”. Next, the multi-value quantization result value increases to “2” when the pixel group gradation value ranges from 21 to 42, and the multi-value quantization result value increases to “3” when the pixel group gradation value ranges from 43 to 69. To do. Thus, as the pixel group gradation value increases, the multi-value quantization result value also increases stepwise, and finally the multi-value quantization result value increases to “15”. That is,
For the pixel group of classification number N1, pixel group gradation values that can take a range of gradation values 0 to 255 are multi-valued (in other words, 16-valued) in 16 levels from gradation values 0 to 15. Will be.

Similarly, for the pixel group with the classification number N2 indicated by the thick broken line in the drawing and the pixel group with the classification number N3 indicated by the thick dashed-dotted line, the pixel group floor that can take the range of the gradation value 0 to 255. The key value
Multi-valued (in other words, 18-valued) is performed in 18 levels from gradation values 0 to 17. Further, for the pixel group of classification number N4 indicated by a thin solid line and the pixel group of classification number N5 indicated by a thin one-dot chain line, the pixel group gradation value is multi-valued in 21 steps from gradation values 0 to 20. (In other words, 21 values)
Will be. Thus, in the first dot data generation process shown in FIG.
The number of stages of multi-value conversion for each pixel group (the number of states that can be taken as multi-value conversion result values) is not the same, and multi-value conversion is performed with a specific number of stages according to the pixel group classification number. As a result, even when the same pixel group gradation value is multi-valued, if the pixel group classification number is different, and therefore the number of multi-value levels is different, the multi-value value is different.

Further, even if the number of multi-value levels is the same, the same pixel group gradation value is not converted to the same multi-value value. For example, a pixel group with classification number N2 shown in FIG.
As is clear from comparison with these pixel groups, the number of multi-value levels for these pixel groups is 18 in all cases. However, in many cases, the pixel group tone value to which the multi-value result value is switched is one. I have not done it. This is because different threshold values are set for the threshold value groups set in the threshold value table shown in FIG. 9 for the classification number N2 and the classification number N3. Similarly, for the pixel group of classification number N4 and the pixel group of classification number N5, the number of multi-value levels of these pixel groups is 21, but the pixel group tone value at which the multi-value quantization result value is switched is Often does not match. For this reason, even if the number of multi-value levels in the pixel group is the same, different multi-value values are obtained if the classification numbers are different.

As described above, in the threshold value table shown in FIG. 9, a unique threshold set is set for each pixel group classification number. Step S20 of the first dot data generation process shown in FIG.
8, the pixel group gradation value of the pixel group is converted into a multi-value quantization result value by referring to the threshold value table shown in FIG. 9 from the pixel group gradation value and the classification number determined for each pixel group. Perform the conversion process. The threshold table setting method shown in FIG. 9 will be described in detail later.

Next, the multi-value quantization result value obtained for each pixel group is converted into number data (step S in FIG. 7).
210). The number data is data representing the number of dots formed in the pixel group. As described above, since the color printer 200 can form three types of dots, large dots, medium dots, and small dots, the number data is data indicating the number of these various dots formed in the pixel group. Become. The conversion from the multi-value quantization result value to the number data can be performed very quickly by referring to a conversion table set in advance.

FIG. 11 is an explanatory diagram conceptually showing a conversion table that is referred to when converting a multi-value quantization result value of a pixel group into number data. As shown in the drawing, as shown in the drawing, in the conversion table, number data corresponding to the multi-value quantization result value is set for each classification number. As an example, a pixel group with classification number 1 will be described. For multi-value quantization result value 0, number data “0” is set. The number data “0” is data representing that the number of large dots, medium dots, and small dots formed is zero. In addition, for multi-value quantization result value 1, number data “1” is set. The number data “1” is data indicating that the number of large dots and medium dots formed is zero and the number of small dots formed is one. Further, the number data “164” is set for the multi-value quantization result value 15. Number data “164”
"Is data representing that eight large dots are formed, and medium and small dots are not formed. For the pixel group with classification number 1, number data is not set for multi-value quantization result values larger than “16”. This corresponds to the fact that the pixel group of classification number 1 has 16 multi-value levels, and the multi-value result value can only take values from 0 to 15. Therefore, for a pixel group with 18 multi-level levels, such as the pixel group of classification number 2, number data is set only for the multi-level result values of 0 to 17, and a number larger than “18” is set. The number data is not set for the valuation result value. FIG. 12 shows the correspondence between the number data and the combination of the number of large dots, medium dots, and small dots represented by the number data.
A method for setting the conversion table as shown in FIG. 11 will be described in detail later with reference to another drawing.

Thus, in the conversion table, data indicating the number of various dots formed in the pixel group is set for each combination of the pixel group classification number and the pixel group gradation value. Therefore, referring to the conversion table, the multi-value quantization result value of the pixel group can be quickly converted into the number data. In step S210 of the first dot data generation process shown in FIG. 7, the multi-value quantization result value for each pixel group is thus converted into number data.

The number data can be any form of data as long as the number of dots formed in the pixel group can be specified by some method. For example, if the number of large dots formed in a pixel group is K, the number of medium dots is L, and the number of small dots is M, “K
It is also possible to use a sequence of numerical values “LM” as the number data. However, instead of such a method, as described above, it is better to associate a numerical value from 0 to 164 with a combination of the number of formed dots for various dots, and to express the number of formed various dots by this numerical value. Therefore, the data amount of the number data can be reduced. Hereinafter, this point will be described.

First, since one pixel group includes 8 pixels, the number of large dots (K), the number of medium dots (L), the number of small dots (M) ) Can take from 0 to 8 values. Therefore, if the numbers of various dots are arranged as they are and expressed as KLM, 4 bits are required to represent the number of large dots, the number of medium dots, and the number of small dots, respectively. The number data is 12-bit data.

On the other hand, since one pixel group is composed of eight pixels, the total number of dots that can be formed in the pixel group is eight at most. For example, a combination of the number of dots such as four large dots, three medium dots, and two small dots cannot be generated in reality because the total number of dots exceeds nine and exceeds eight. . Focusing on these points, it is considered that there are not so many kinds of combinations of the number of dots that can actually occur. The actual calculation is as follows. The pixel group includes eight pixels. For each pixel, “form a large dot”, “form a medium dot”, “form a small dot”, “do not form a dot” 4 It can take two states. Therefore, the combination of the number of dots that can be formed in the pixel group is equal to the number of combinations when these four states are selected eight times with allowance for overlap.
₄ H ₈ (= _{4 + 8-1} C ₈ )
As a result, only 165 combinations at most appear. Here, _n H _r is an operator for obtaining the number of overlapping combinations when r times are selected from n objects by allowing duplication. _N C _r is an operator for obtaining the number of combinations when selecting r times from n objects without allowing duplication. If there are 165 combinations, 8 bits can be expressed. Therefore, if a code number is set for a combination of the number of dots that can actually occur, the combination of the number of dots to be formed in the pixel group can be represented by 8-bit data. In the end, if the number of dots formed is represented by the correspondence as shown in FIG. 12, it is possible to reduce the data amount of the number data rather than arranging the number of dots formed for each dot type. This makes it possible to reduce the data amount of the conversion table in which the number data is set for each combination of the classification number and the multi-value quantization result value.

When the multi-value quantization result value of the pixel group is converted into the number data as described above (step S210 in FIG. 7), the number data is once converted into intermediate data (step S212). That is, as preparation for converting the number data obtained for each pixel group into dot data,
The process of changing to a data format that is easier to convert is performed.

The conversion from the number data to the intermediate data can be quickly executed by referring to a preset correspondence table. FIG. 13 is an explanatory diagram showing a correspondence table in which the number data and the intermediate data are associated with each other. As shown in the figure, in the conversion table, corresponding intermediate data is set for each number data, and each intermediate data is 16-bit data. Here, the reason why the data length of the intermediate data is 16 bits is that the number of pixels included in the pixel group is 8, and the types of dots that can be formed are large, medium, and small. This is because the presence or absence of dot formation can be expressed with 2 bits for each. That is, the intermediate data is data that represents the presence or absence of dot formation for each pixel, using 8 sets of data corresponding to the number of pixels, with 2 bits each as one set. This will be specifically described with reference to FIG.

For example, the number data “1” indicates a combination of 0 large dots, 0 medium dots, and 1 small dot. For reference, on the right side of FIG. 13, combinations of dot numbers indicated by the respective number data are shown. If the 2-bit data representing a small dot is “01”, the 16-bit data corresponding to the number data “1” includes only one set of “01”, and the other 7 sets of 2-bit data. Becomes data such as “00”. The 2-bit data “00”
"Is data indicating that dots are not formed.

Similarly, the number data “163” indicates a combination of seven large dots, one medium dot, and zero small dots. If the 2-bit data representing the large dot is “11” and the 2-bit data representing the medium dot is “10”, the 16-bit data corresponding to the number data “163” is the 2-bit data “11”. Are included, and the data includes one set of 2-bit data “10”.

These 2-bit data are set right-justified in the order of large dots, medium dots, and small dots. For example, the combination of the number of dots is one large dot, two medium dots, and three small dots.
If there are two pieces of data, 8 bits of 2-bit data, 2 bits of data representing a large dot “1”
“1” is set only at the right end, and next to the left, two-bit data “1” representing a medium dot is set.
Two sets of “0” are set, and three sets of 2-bit data “01” representing small dots are set to the left of the two sets, and the remaining two sets of 2-bit data “0” indicating that dots are not formed. 00 "
Will be set. However, these 2-bit data may be set left justified. That is, the order may be set from the left in the order of large dots, medium dots, and small dots.

In step S212 of the first dot data generation process shown in FIG. 7, a process for converting the number data obtained for each pixel group into intermediate data by referring to the conversion table shown in FIG. If the number of various dots formed in the pixel group is expressed in such a format, it becomes easy to correspond to the pixels as will be described later, and therefore it is possible to easily determine whether or not dots are formed.

In this embodiment, by referring to the conversion table shown in FIG. 11, the multi-value quantization result value obtained for each pixel group is once converted into number data, and then the number data is converted into intermediate data. Yes. However, as shown in FIG. 13, there is a one-to-one correspondence between the number data and the intermediate data, and the intermediate data can be determined immediately after the number data is determined.
In the conversion table shown in FIG. 1, intermediate data may be set instead of the number data, and the intermediate data may be immediately obtained from the multi-value quantization result value by referring to the conversion table. In this way, the trouble of converting the number data into intermediate data can be saved, so that dot data can be generated quickly. However, since the intermediate data has a data length longer than that of the number data, if intermediate data is set in the conversion table instead of the number data, the amount of data for storing the conversion table increases. That is, in this embodiment, the number data has a data length of 1 byte, whereas the intermediate data is data of 2 bytes. Therefore, the conversion table in which the number data is set is half of the conversion table in which the intermediate data is set. It is possible to store in the memory capacity.

When the intermediate data is acquired as described above, the order value matrix corresponding to the pixel group is read, and processing for determining whether or not to form dots for each pixel in the pixel group is performed (step S214). Here, the order value matrix is a matrix in which the order in which dots are formed is set for each pixel in the pixel group.

FIG. 14 is an explanatory diagram illustrating an order value matrix. As shown in the figure, the order value matrix is also set to a different matrix for each pixel group classification number. As an example, the order value matrix of classification number 1 shown in FIG. In the pixel group with classification number 1, the pixel at the upper left corner is set as the pixel in which the dot is most easily formed among the eight pixels constituting the pixel group. The numerical value “
“1” is set to indicate that this pixel is a pixel in which a dot is formed first. A numerical value representing such an order set in the order value matrix is referred to as an order value. In addition, the order value “2” is set for the pixel in the lower right corner of the pixel group. This is because the second dot in the pixel group is likely to be formed in the pixel group (therefore, the second dot in the pixel group is formed). Is formed). As described above, in the order value matrix, order values indicating the order in which dots are formed are set for the eight pixels included in the pixel group.

Such an order value matrix differs depending on the pixel group classification number. For example, in the order value matrix of classification number 2 shown in FIG. 14B, the pixel in which the first dot is formed (the pixel with the order value “1”) is the second pixel from the left in the lower row. The pixel on which the second dot is formed (the pixel having the order value “2”) is the pixel in the lower right corner.
In the order value matrix of classification number 3 shown in FIG. 14C, the pixel in which the first dot is formed (the pixel with the order value “1”) is the second pixel from the right on the upper stage, and 2 The pixel in which the dot is formed in the second order (the pixel having the order value “2”) is the pixel in the lower left corner. A method for setting the order value matrix for each pixel group classification number will be described in detail with reference to another drawing.

In the ROM mounted on the control circuit 260 of the color printer 200, an order value matrix as illustrated in FIG. 14 is stored in advance for each pixel group classification number. When determining whether or not to form dots for each pixel from the intermediate data of the pixel group, the order value matrix corresponding to the pixel group classification number is read out and the following processing is performed.

FIG. 15 shows that by reading the data corresponding to the sequence value from the intermediate data,
It is explanatory drawing which showed a mode that the presence or absence of dot formation was determined. FIG. 15A exemplifies intermediate data obtained by converting the number data for a certain pixel group. As described above, the intermediate data is 16-bit data, and is composed of 8 sets of 2 bits each. The intermediate data shown in FIG. 15A includes two sets of 2-bit data “11” representing a large dot, two sets of 2-bit data “10” representing a medium dot, and two bits representing a small dot. “01” is 3 sets, and 2-bit data “00” indicating that a dot is not formed is 2
A set is included, and these 2-bit data are set right-justified in the order of large dots, medium dots, and small dots.

Assume that the pixel group classification number is number 1. The order value matrix of classification number 1 is
It is shown in FIG. From this pixel group, one pixel for determining whether or not to form dots is selected. Here, it is assumed that the pixel in the upper left corner of the pixel group is selected. According to the order value matrix, the order value of this pixel is “1”. Therefore, by reading out the 2-bit data set at the right end in the intermediate data shown in FIG. 15A, the type of dot to be formed on this pixel can be determined. In the example shown in FIG.
Since the 2-bit data set at the right end is “11”, a large dot is formed in this pixel.

Next, the order value “6” is set in the order value matrix of FIG. 14A for the pixel on the right (second pixel from the left in the upper stage), and therefore the order value “6” in FIG. 15A is set. If the 2-bit data set in the sixth set from the right is read out from the intermediate data, the type of dot to be formed on the pixel having the order value 6 can be determined. FIG. 15B conceptually shows a state in which 2-bit data in the sixth set from the right end of the intermediate data is read. In the illustrated example, since the read 2-bit data is “01”, a small dot is formed in this pixel.

In the above description, it is assumed that the location where 2-bit data is read in the intermediate data is changed according to the order value. However, instead of changing the location to be read in the intermediate data,
The location where data is read may be fixed, and the intermediate data may be shifted by the number of pairs corresponding to the order value. Even in this way, it is possible to determine the presence or absence of dot formation. FIG. 15C is an explanatory diagram conceptually showing a state in which the presence / absence of dot formation is determined by shifting intermediate data. In the example shown, the 2-bit data at the right end of the intermediate data is read out, and the intermediate data is shifted rightward by the number of sets corresponding to the order value of the pixels (specifically, the number of sets less by 1 from the order value). I am letting. FIG. 15 (b) and FIG. 15 (c)
As is clear from comparison between the two, the two-bit data set at the same location in the intermediate data is eventually read out regardless of which operation is performed. Since the process of shifting the data by a predetermined number of bits can be performed at a relatively high speed, if the intermediate data is shifted in this way, the 2-bit data at the location corresponding to the sequence value can be read quickly. The presence or absence of dot formation for the pixel of interest can be quickly determined.

FIG. 16 is an explanatory diagram showing how the intermediate data of FIG. 15A is applied to the respective order value matrices shown in FIG. 14 to determine whether or not dots are formed for each pixel in the pixel group. is there. As described above, whether or not a dot is formed for each pixel in the pixel group is determined by the intermediate data obtained for the pixel group and the order value matrix stored in association with the pixel group classification number. Therefore, even if the intermediate data has the same value, if the pixel group classification numbers are different, different arrangements of dots are formed in the pixel group.

As described above, referring to the intermediate data obtained by converting the number data and the order value matrix, which dot is formed for each pixel in the pixel group, or which dot is not formed, It can be determined by a simple operation. In step S214 of the first dot data generation process shown in FIG. 7, the process for determining whether or not to form dots is performed for each pixel in the pixel group in this way.

When the presence / absence of dot formation is determined for all the pixels in the pixel group in this way, it is determined whether the above-described series of processing has been performed for all the pixels (step S216). If unprocessed pixels remain (step S216: no), the process returns to step S204 to generate a new pixel group, and then a series of processes are performed to obtain each pixel in the pixel group. The presence or absence of dot formation is determined. Such processing is repeated, and if it is determined that the processing has been completed for all pixels (step S216: yes), the obtained dot data is output to the ink ejection head (step S218). Then, the first dot data generation process shown in FIG. 7 is terminated, and the process returns to the image printing process of FIG. As described above, in the image printing process, ink droplets are ejected according to the output dot data, whereby dots are formed on the printing paper and the image is printed.

The general procedure of the first dot data generation process for receiving the image data from the digital camera 120 and generating the dot data has been described above. Next, the meaning of these procedures and the reason why image data can be converted into dot data by such procedures will be described.

D-2. Pixel group classification number:
As described above, in the first dot data generation process, the number of pixels is further increased both when the pixel group gradation value is converted into a multivalued result value and when the multivalued result value is converted into number data. When determining the presence or absence of dot formation for each pixel in the pixel group from the intermediate data obtained by converting the data, processing is performed using the pixel group classification number. First, the meaning of the pixel group classification number will be described in detail.

As described above, the pixel group classification number simply means that when determining the presence or absence of dot formation for each pixel in the pixel group using the dither matrix, which part of the dither matrix is the pixel group. It is a number indicating whether it is applied to. FIG. 17 is an explanatory diagram illustrating an enlarged part of the dither matrix. The illustrated matrix includes 128 pixels in the horizontal direction (main scanning direction), 64 pixels in the vertical direction (sub-scanning direction), a total of 8192 pixels, and a gradation value of 1
A threshold value uniformly selected from the range of ˜255 is randomly stored. Here, the threshold gradation value is selected from the range of 1 to 255, in addition to the fact that, in this embodiment, the image data is 1-byte data that can take a gradation value of 0 to 255. This is because, when the gradation value of the image data is equal to the threshold value, it is determined that a dot is formed in the pixel.

That is, if the dots are formed only in pixels whose gradation value of the image data is larger than the threshold value (that is, dots are not formed in pixels where the gradation value and the threshold value are equal), the image data can be taken. A dot is never formed on a pixel having a threshold value equal to the maximum gradation value. In order to avoid such a situation, the range that can be taken by the threshold is a range obtained by removing the maximum gradation value from the range that can be taken by the image data. On the other hand, when dots are formed even in pixels where the gradation value of the image data is equal to the threshold value, dots are always formed in the pixels having the same threshold value as the minimum gradation value that the image data can take. It will end up. To avoid this,
The range that can be taken by the threshold is a range obtained by removing the minimum gradation value from the range that can be taken by the image data.
In this embodiment, the gradation values that the image data can take are 0 to 255, and dots are formed in pixels that have the same threshold as the image data. Therefore, the range that the threshold can take is set to 1 to 255. is there. Note that the size of the dither matrix is not limited to the size illustrated in FIG. 17 and can be various sizes including a matrix having the same number of vertical and horizontal pixels.

FIG. 18 is an explanatory diagram conceptually showing a state in which the presence / absence of dot formation for each pixel is determined with reference to the dither matrix. In determining the presence or absence of dot formation, first, the pixel to be determined is selected, the gradation value of the image data for this pixel,
The threshold value stored in the corresponding position in the dither matrix is compared. The thin broken arrow shown in FIG. 18 schematically represents that the gradation value of the image data and the threshold value stored in the dither matrix are compared for each pixel. For example, for the pixel in the upper left corner of the image data, the gradation value of the image data is 97 and the threshold value of the dither matrix is 1, so it is determined that a dot is formed on this pixel. An arrow indicated by a solid line in FIG. 18 schematically represents a state in which it is determined that a dot is to be formed in this pixel and the determination result is written in the memory. On the other hand, for the pixel on the right side of this pixel, the gradation value of the image data is 97, and the threshold value of the dither matrix is 177. Since the threshold value is larger, it is determined that no dot is formed for this pixel. In the dither method, the image data is converted into data representing the presence / absence of dot formation for each pixel by determining whether or not to form dots for each pixel while referring to the dither matrix. Based on the content described above, the following describes the meaning of the pixel group classification number and the concept of determining the classification number.

FIG. 19 is an explanatory diagram showing the content of the classification number for each pixel group. For the sake of specific explanation, here, a total of eight pixels, ie, four pixels in the main scanning direction (horizontal direction on the paper surface) and two pixels in the sub-scanning direction (vertical direction on the paper surface) are grouped as a pixel group. As shown in FIG. 19 (a), description will be made by paying attention to the pixel group at the upper left corner of the image.

As described above, in the dither method, the tone value of the image data assigned to the pixel is compared with the threshold value set at the corresponding position in the dither matrix, and the presence or absence of dot formation is determined for each pixel. Yes. On the other hand, in the present embodiment, since a predetermined number of adjacent pixels are grouped as a pixel group, a predetermined number of blocks corresponding to the pixel group are also generated for the threshold values set in the dither matrix. . FIG. 19B shows a state in which a plurality of blocks are generated by collecting four threshold values set in the dither matrix shown in FIG. 17 and two in the vertical direction. The dither matrix shown in FIG.
Since thresholds for a total of 8192 pixels are set for 128 pixels in the main scanning direction and 64 pixels in the vertical direction (sub-scanning direction), the thresholds are set to 4 in the horizontal direction and 2 in the vertical direction. In summary, the dither matrix is divided into a total of 1024 blocks, 32 each in length and width.

Now, as shown in FIG. 19B, serial numbers from 1 to 1024 are assigned to these blocks. Then, when the dither matrix is applied to the image data, the pixel groups are classified according to the serial numbers of the blocks applied to the positions of the pixel groups. For example, FIG.
As shown in FIG. 19B, since the block having the serial number 1 in FIG. 19B is applied to the pixel group at the upper left corner of the image, this pixel group is classified into the pixel group having the classification number 1. being classified. As described above, the pixel group classification number represents which block in the dither matrix is applied to the pixel group.

Next, the reason why the pixel group classification number can be calculated by the method described above with reference to FIG. 8 will be described. FIG. 20 is an explanatory diagram showing a method for calculating a pixel group classification number. FIG.
(A) represents one pixel group generated in the image. Hereinafter, a method for calculating a classification number using this pixel group as a target pixel group will be described. As described above, the position of the pixel group of interest is represented by the pixel position of the pixel at the upper left corner of the pixel group. FIG. 20 (a)
In the figure, pixels indicating the position of the pixel group are displayed with black circles. The pixel position of this pixel is (X
, Y). Then, since the size of each pixel group is 4 pixels in the main scanning direction and 2 pixels in the sub scanning direction,
X = 4n + 1, Y = 2m + 1
N and m (where n and m are positive integers greater than or equal to 0) exist. In other words, n pixel groups are arranged on the left side of the pixel group of interest, and m pixel groups are arranged above the pixel group of interest.

Here, as described above, the pixel group is classified based on the serial number of the block applied to the pixel group of interest when the dither matrix is applied to the image data (
According to the method applied to the image data while moving the dither matrix, the same pixel group is classified into different classification numbers (see FIG. 19). In practice, any method may be used for applying the image data while moving the dither matrix, but here, for convenience of explanation, the simplest method, that is, the dither matrix is described as moving horizontally. . FIG. 20B conceptually shows how the dither matrix is repeatedly applied to the image data while being gradually moved in the horizontal direction.

FIG. 20C conceptually shows how the dither matrix is applied to the pixel group of interest shown in FIG. 20A while repeatedly using the dither matrix as shown in FIG. Yes. When the dither matrix is moved in this way, any block in the dither matrix is applied to the target pixel group. Here, it is assumed that the block of the Mth row and the Nth column in the dither matrix is applied to the pixel group of interest. Then
As shown in FIG. 20 (a), there are n pixel groups on the left side of the target pixel group and m pixel groups on the upper side. , N = n−int (n / 32) × 32 + 1
M = m−int (m / 32) × 32 + 1
The relationship is established. Here, int is an operator representing rounding down to the integer. That is, int (n / 32) represents an integer value obtained by rounding down the numerical value after the decimal point to the calculation result of n / 32. Thus, if the position of the pixel group of interest is known, numerical values M and N are obtained from the above-described relational expression displayed in FIG. The classification number of the pixel group of interest may be used. However, in practice, as described above with reference to FIG. 8, the data can be obtained very simply by extracting predetermined bit data from the data in which the coordinate values X and Y of the pixel group of interest are displayed in binary. Hereinafter, this reason will be described.

FIG. 21 is an explanatory diagram showing a method for obtaining the classification number from the binary display of the coordinate value of the pixel group of interest. Assume that the coordinate value of the pixel group of interest is (X, Y), and X and Y are expressed by 10 bits. FIG. 21A conceptually shows 10-bit binary data representing the numerical value X. In the figure, a 1 from the most significant bit to the least significant bit is used to identify each bit.
The serial numbers from No. 10 to No. 10 are attached and displayed.

As described above with reference to FIG. 20, the number n of pixel groups on the left side of the pixel group of interest can be obtained by subtracting 1 from the numerical value X and dividing by 4. Here, the division by 4 can be performed by shifting rightward by 2 bits, so 1 is subtracted from the numerical value X, and the binary data obtained is only 2 bits rightward. A bit shift may be performed. Furthermore, the numerical value X
Can take only a numerical value that can be expressed in the form of 4n + 1, not an arbitrary value.
Without subtracting, simply shifting the binary data to the right by 2 bits,
The number n of pixel groups can be obtained. FIG. 21B conceptually represents the number n of binary number data obtained by bit shifting the numerical value X in this way.

Next, int (n / 32) is calculated. That is, an operation of dividing the number n by 32 and truncating the numerical value after the decimal point is performed. The division by 32 can be executed by shifting the binary data to the right by 5 bits, and if the data is handled in integer format, the numerical value after the decimal point is automatically truncated. . Eventually, binary data of int (n / 32) can be obtained by simply shifting the number n of binary data by 5 bits in the right direction. FIG. 21 (c) shows the in obtained by bit shifting the number n.
The binary data of t (n / 32) is conceptually represented.

The int (n / 32) obtained in this way is multiplied by 32. Multiplication by 32 can be performed by bit-shifting binary data to the left by 5 bits. FIG.
d) conceptually represents int (n / 32) × 32 binary data obtained by bit-shifting the number n.

Next, the above-described numerical value N can be obtained by subtracting int (n / 32) × 32 from the number n. Number n binary data (see FIG. 21B) and int (n / 32) × 32 2
As is clear from comparison with the decimal data (see FIG. 21 (d)), these binary data have the same upper 5 bits, and all the lower 5 bits of the numerical value to be subtracted are “0”. It has become. Therefore, if the lower 5 bits of the subtracted numerical value (number n) are extracted as they are,
The desired numerical value M can be obtained. That is, it is possible to obtain the numerical value N very simply by applying the mask data as shown in FIG. 21F to the binary data shown in FIG. More simply, the mask data as shown in FIG. 21G is applied to the binary data of the numerical value X indicating the position of the pixel group of interest shown in FIG. The numerical value N can also be obtained by directly extracting the bit data.

In FIG. 21, the case where the numerical value N indicating the block position in the dither matrix is obtained from the numerical value X of the coordinate values (X, Y) indicating the position of the pixel group of interest has been described. The indicated numerical value M can also be obtained from the numerical value Y. After all, if the position of the pixel group of interest is known, it is possible to know how many rows and columns correspond to the pixel group of interest in the dither matrix simply by extracting data at a specific bit position from the binary data. If the serial number of this block is calculated, the classification number of the pixel group of interest can be obtained. The classification number calculation method described above with reference to FIG. 8 is a method derived in this manner.

D-3. Threshold table setting method:
As described above with reference to FIG. 7, in the first dot data generation process, after obtaining the classification number in this way, the pixel group gradation value is obtained by referring to the threshold value table by combining the pixel group gradation value and the classification number. Is converted to a multi-value quantization result value. As shown in FIG. 9, a threshold set is set for each classification number in the threshold table, and the pixel group gradation is compared with the threshold set in the threshold set and the pixel group gradation value. The value is converted into a multi-value quantization result value. That is, it is important to set an appropriate threshold value table in order to appropriately convert the pixel group gradation value into the multi-value quantization result value. In the following, a method for setting the threshold value table shown in FIG. 9 will be described.

The threshold value table of this embodiment is set based on a technique developed from the dither method described above so that the presence or absence of dot formation can be determined for each pixel for a plurality of types of dots having different sizes. The detailed contents of this method are disclosed in Japanese Patent No. 3292104. Before describing the threshold value table setting method, as a preparation, an outline of the technique disclosed in the above-mentioned patent publication will be briefly described.

FIG. 22 is a flowchart showing the flow of halftone processing in which the dither method is developed so that the presence / absence of formation of large dots, medium dots, and small dots can be determined for each pixel. When halftone processing is started, first, select a pixel to be determined whether or not dots are formed,
Image data of the pixel is acquired (step S250). Next, the acquired image data is converted into density data for large, medium, and small dots. Here, the density data is data representing the density at which dots are formed. The density data indicates that dots are formed at a higher density as the gradation value increases. For example, the gradation value “2” of the density data
“55” indicates that the dot formation density is 100%, that is, dots are formed in all pixels. The gradation value “0” of the density data indicates that the dot formation density is 0%, that is, This indicates that no dot is formed on the pixel. Such conversion into density data can be performed by referring to a numerical table called a dot density conversion table.

FIG. 23 is an explanatory diagram conceptually showing a dot density conversion table that is referred to when the gradation value of the image data is converted into density data for large, medium, and small dots. As shown in the figure, in the dot density conversion table, small dots, medium dots,
Density data for each large dot is set. Image data has a gradation value of “0”
In the neighboring area, the density data of medium dots and large dots are both set to the gradation value “0”. The density data of small dots increases as the gradation value of the image data increases, but when the image data reaches a certain gradation value, it starts to decrease and the density data of medium dots increases instead. Begin to. When the gradation value of the image data further increases and reaches a certain gradation value, the density data of the small dots becomes the gradation value “0”, the density data of the medium dots starts to decrease, and instead the density of the large dots Data increases little by little. In step S252 in FIG. 22, the gradation value of the image data is converted to large dot density data, medium dot density data, and small dot density data while referring to this dot density conversion table.

When the density data of the large, medium, and small dots is obtained for the pixel to be processed, it is first determined whether or not large dots are formed (step S254 in FIG. 22). Such judgment is
This is done by comparing the density data of the large dots with the threshold value of the dither matrix set at the corresponding position of the pixel to be processed. If the density data of large dots is larger than the threshold value, it is determined that large dots are to be formed on the pixel to be processed. Conversely, if the density data is smaller, it is determined that no large dots are formed.

Next, it is determined whether or not it is determined to form a large dot on the pixel to be processed (step S256). If it is determined to form a large dot (step S256: yes).
s) The determination of medium dots and small dots is omitted, and it is determined whether or not all pixels have been completed (step S268). If there remains a pixel for which dot formation has not been determined (step S268: no), the process returns to step S250 to select a new pixel and perform a series of subsequent processing.

On the other hand, if it is not determined that a large dot is to be formed on the pixel to be processed (step S2
56: no), in order to determine whether medium dots are formed or not, medium dot density data is added to the large dot density data to calculate intermediate data for medium dots (step S258).
. The intermediate data for medium dots thus obtained is compared with the threshold value of the dither matrix. If the intermediate data for medium dots is larger than the threshold, it is determined that a medium dot is formed. Conversely, if the threshold of the dither matrix is larger than the intermediate data, no medium dot is formed. Judgment is made (step S260).

Next, it is determined whether or not it is determined to form a medium dot in the pixel to be processed (step S262). If it is determined to form a medium dot (step S262: yes).
s) The determination of small dots is omitted, and it is determined whether or not all pixels have been completed (step S268).

If it is not determined that a medium dot is to be formed in the pixel to be processed (step S262:
no) In order to determine whether or not the small dot is formed, the small dot intermediate data is calculated by adding the density data of the small dot to the intermediate data for the medium dot (step S264). Then, the obtained intermediate data for small dots is compared with the threshold value of the dither matrix. As a result, if the intermediate data for small dots is larger than the threshold value, it is determined that a small dot is formed. Conversely, if the dither matrix threshold value is larger than the intermediate data, no dot is formed. Judgment is made (step S266).

That is, for a pixel having a larger threshold set in the dither matrix than the large dot density data (a pixel in which no large dot is formed), it is obtained by adding the medium dot density data to the large dot density data. The intermediate data is compared with the threshold value, and if the intermediate data becomes larger, it is determined that a medium dot is formed. On the other hand, for pixels whose threshold is still larger than that of the intermediate data, new intermediate data is calculated by adding density data of small dots to the intermediate data. Then, the intermediate data is compared with the threshold value, and if the new intermediate data is larger, it is determined that a small dot is to be formed, and it is determined that no dot is formed for a pixel having a still larger threshold value. is there.

By performing the processing as described above, large dots, medium dots,
It is possible to determine which of small dots is formed or whether any dot is not formed. Therefore, it is determined whether or not the processing has been completed for all the pixels (step S268). If there are any undetermined pixels remaining (step S268: no), the process returns to step S250 to select a new pixel, A series of subsequent processing is performed. In this manner, it is determined whether large, medium, or small dots are to be formed one by one for the pixel selected as the processing target. If it is determined that the processing has been completed for all pixels (step S26).
8: yes), the halftone process shown in FIG. 22 is terminated.

The method for determining the presence / absence of formation for each large, medium, and small dot using the dither matrix has been described above. In the following, based on the above description, a setting method of the threshold table shown in FIG. 9 will be described.

As described above, in the multi-value quantization result value generation process, the pixel group is collectively multi-valued by representing the image data of each pixel included in the pixel group by the pixel group tone value. Therefore, when setting the multi-value conversion table, first, assuming that all pixels in the pixel group have image data having the same value as the pixel group gradation value, whether or not various large, medium, and small dots are formed for each pixel. Think about judging. The determination of whether or not various dots are formed is performed by the halftone process described above with reference to FIG.

FIG. 24 is an explanatory diagram conceptually showing a state in which the presence / absence of large / medium / small dots is determined for each pixel in the pixel group. In the drawing, a pixel group of interest for performing halftone processing is surrounded by a thick solid line. The pixel group is composed of eight pixels, and the image data of each pixel has the same value as the pixel group gradation value (gradation value 97 in the illustrated example). In order to determine whether large, medium, or small dots are formed, the image data is converted into density data for each dot. Conversion to density data is performed by referring to the dot density conversion table shown in FIG. Here, since all the pixels in the pixel group have the same image data, all of the various dots and the density data have the same value for the pixels. In the illustrated example, the gradation value of the density data for large dots is “2”, the gradation value of the density data for medium dots is “95”, and the gradation value of the density data for small dots is “30”. Represents.

Next, as described with reference to the flowchart of FIG. 22, by comparing the density data for large dots, the intermediate data for medium dots, or the intermediate data for small dots with the threshold value set in the dither matrix. Whether or not various dots are formed is determined for each pixel. Here, as the threshold value of the dither matrix used for comparison, a threshold value set in a location corresponding to the pixel group of interest is used from the dither matrix. For example, FIG.
In the example shown in FIG. 4, since the pixel group is in the upper left corner of the image, the threshold value set in the upper left corner pixel group in the dither matrix is also used as the threshold value.

Then, among the eight threshold values set for the pixel group, it is determined that a large dot is formed for a pixel for which a threshold value smaller than the large dot density data is set. Here, since the density data of the large dots is the gradation value “2”, the pixels where the large dots are formed are only the pixels for which the threshold value “1” is set. In FIG. 24, the pixels for which large dots are determined to be formed are displayed with fine diagonal lines. Pixels that are larger than the large dot density data “2” and have a smaller threshold than the medium dot intermediate data “97” obtained by adding the large dot density data and the medium dot density data. Is determined to form a medium dot. There are only two such pixels, a pixel for which the threshold “42” is set and a pixel for which the threshold “58” is set. In FIG. 24, pixels that are determined to have medium dots formed are displayed with a slightly rough diagonal line. Finally, it is larger than intermediate data “97” for medium dots, and smaller than intermediate data “127” for small dots obtained by adding density data for small dots to intermediate data for medium dots. It is determined that a small dot is formed in a pixel for which a threshold is set. Such pixels are only those for which the threshold value “109” is set. In FIG. 24, the pixels for which small dots are determined to be formed are displayed with rough diagonal lines. In this way, when the pixel group gradation value of the pixel group of interest is “97” as a result of determining whether large dots, medium dots, and small dots are formed, large dots 1
One, two medium dots, and one small dot are formed.

If the pixel group tone value is greatly different, the numbers of large dots, medium dots, and small dots formed in the pixel group are also different. Further, if the pixel group gradation value is changed from “0” to “255”, the number of large dots, medium dots, and small dots should be changed in several steps. Furthermore, if the pixel group classification number is different, the dither matrix threshold value is also different, so the manner of changing the number of dots should be different. The threshold value table shown in FIG. 9 is set by examining the behavior in which the number of various dots changes step by step when the pixel group gradation value is changed from “0” to “255”. Has been.

FIG. 25 is a flowchart showing the flow of processing for actually setting the threshold value table. Hereinafter, it demonstrates according to a flowchart. When the threshold table setting process is started, first, one pixel group classification number is selected (step S300). For example, it is assumed here that classification number 1 is selected.

Next, the threshold corresponding to the pixel group of the selected classification number is read out from the dither matrix (step S302). For example, since classification number 1 is selected here, eight threshold values set at the block position indicated as number 1 in FIG. 19B are selected from the dither matrix illustrated in FIG. read out.

Then, the pixel group tone value BD is set to “0” (step S304), and the number of large dots, medium dots, and small dots formed is set to 0 (step S306).

Subsequently, by referring to the dot density conversion table shown in FIG. 23, the pixel group gradation value is converted into density data for large dots, medium dots, and small dots (step S308).
) Based on these density data and the threshold value read in advance, the number of formations for various large, medium, and small dots is determined (step S310). That is, as described with reference to FIG. 22 or FIG. 24, the number of threshold values smaller than the large dot density data is obtained, and the obtained number is used as the large dot formation number. Further, the number of threshold values larger than the density data for large dots and smaller than the intermediate data for medium dots is obtained, and this is set as the number of medium dots formed. Further, the number of thresholds larger than the intermediate data for medium dots and smaller than the intermediate data for small dots is obtained, and this is used as the number of small dots formed.

It is determined whether or not the number of dots formed in this way has been changed with respect to the number of dots previously set (step S312). If it is determined that the number of formations has been changed (step S312: yes), the pixel group gradation value BD at that time is set as a new threshold value.
It adds to the group of the threshold value corresponding to a classification number (step S314). On the other hand, when it is determined that the number of formations has not been changed (step S312: no), the process of adding a threshold is skipped.

Next, it is determined whether or not the pixel group gradation value BD has reached the gradation value 255 (step S31).
6). If the gradation value 255 has not been reached (step S316: no), the pixel group gradation value BD
Is increased by “1” (step S318), and the process returns to step S308 to convert the pixel group gradation value BD into density data again, and then a series of processes are performed to determine the number of dots formed in the pixel group. Is changed, the pixel group gradation value BD is added as a new threshold value to the threshold value corresponding to the classification number (step S314). Such an operation is repeated until the pixel group gradation value BD reaches the gradation value 255. When the pixel group gradation value BD reaches the gradation value 255 (step S316: yes), the setting of the threshold set has been completed for the selected classification number.

Therefore, it is determined whether or not the above processing has been performed for all the classification numbers (step S320). If there is an unprocessed classification number (step S320: no), the process returns to step S300 and again. The above-described processing is performed. If it is determined that such a process is repeated and setting of threshold sets has been completed for all classification numbers (step S320: yes).
Then, the threshold table setting process shown in FIG.

As is clear from the above description, the threshold number group of the classification number is obtained by detecting a pixel group gradation value in which the combination of the number of dots formed in the pixel group is switched and storing this value as the threshold value. It has become. Usually, while the pixel group gradation value increases from the gradation value 0 to 255, the number of dots to be formed is switched in several stages, and thus a plurality of threshold values are stored as a set of threshold values. . In each threshold set, a different threshold is set for each classification number and the number of thresholds is different for the following reasons.

First, the number of dots formed in the pixel group is stored in the density data of the large, medium, and small dots obtained by converting the pixel group gradation value and the position corresponding to the pixel group in the dither matrix. And a threshold value. Here, since the dot density conversion table shown in FIG. 23 refers to the same table even if the pixel group classification numbers are different, the density data of each dot for the pixel group gradation value is the same regardless of the classification number. Density data is obtained. However, the plurality of threshold values read from the dither matrix are different for each classification number. Because,
The dither matrix can be made with the dither matrix thresholds dispersed as much as possible so that the dots do not occur in a fixed pattern on the image, or do not deteriorate the image quality due to the formation of dots in close proximity. Only randomly set. For this reason,
Even if the pixel group gradation values are the same, the dot generation method differs for each pixel group and for each pixel group, and as a result, the set threshold value also differs for each category number. It becomes.

However, when the pixel group tone value is increased from 0 to 255, the types of dot distribution that can occur in one pixel group include the number of pixels included in the pixel group and the number of dots that can be formed in each pixel. Depending on the type, there is an upper limit on the number. As described above, the threshold value stored in the threshold group is a pixel group tone value when the dot distribution formed in the pixel group is switched, and is thus set to the threshold group. The number of thresholds also has an upper limit depending on the size of the pixel group and the types of dots that can be formed. As in the present embodiment, when the size of the pixel group is eight pixels and there are three types of dots that can be formed, the number of thresholds set for one threshold group is at most. It is not more than 30 even if it is estimated by 20 or more. Accordingly, the multi-value quantization result value of the pixel group can only take a range of 0 to 31 at most, and such multi-value quantization result value can be expressed with 5 bits.

D-4. How to set the conversion table:
Next, the conversion table setting method described above will be described with reference to FIG. This conversion table is a table that is referred to in order to convert the multi-value quantization result value into number data representing the number of dots formed in the pixel group during the first dot data generation processing shown in FIG. .

As is clear from the threshold table setting method described above with reference to FIG. 25, the threshold group set for each classification number in the threshold table switches the number of large, medium, and small dots formed in the pixel group. The pixel group gradation value is stored. Then, the multi-value quantization result value obtained by referring to the threshold value table is a value representing the number of stages in which the number of dots formed corresponds to the state. However, as described above, the occurrence state of each large, medium, and small dot differs depending on the pixel group classification number, so that only the gradation value that changes the number of dots formed when the pixel group gradation value is increased. In addition, the method of changing the number of formations is also different. For example, in a pixel group of a certain classification number, small dots are formed first, and the number of small dots increases by one as the pixel group gradation value increases, whereas pixels of other classification numbers In a group, dots are not easily formed, medium dots are suddenly formed, and thereafter small dots may increase one by one as the pixel group gradation value increases. That is, the multi-value quantization result value of the pixel group cannot be converted into the number of dots formed in the pixel group unless combined with the pixel group classification number. Therefore, in the first dot data generation process described above with reference to FIG. 7, the number of various dots formed in the pixel group is obtained for each combination of the multi-value quantization result value and the classification number. The number data is immediately obtained from the multi-value quantization result value and the classification number by storing in the conversion table shown and referring to this conversion table.

As is clear from the above description, the conversion table shown in FIG. 11 indicates the number of dots formed in each pixel in the pixel group when having a certain multi-value quantization result value for each pixel group classification number. Is set by asking. Hereinafter, a specific method for setting the conversion table will be described.

FIG. 26 is a flowchart showing a flow of processing for setting a conversion table. Less than,
It demonstrates according to a flowchart. When the conversion table setting process is started, first, one classification number to be set is selected (step S400), and the multi-value quantization result value RV is set to 0 (step S402).

Next, in the threshold table shown in FIG. 9, a threshold corresponding to the multi-value quantization result value RV is acquired from the threshold set set in the classification number (step S404). For example, it is assumed that the multi-value quantization result value is “N”. The multi-value quantization result value N is such that the number of dots formed in the pixel group is N
Since it means that it has switched to the second time, the Nth smallest value is acquired in the threshold set. When the multi-value quantization result value is “0”, the threshold value “0” may be acquired.

Next, assuming that the pixel group tone value of the pixel group has the acquired threshold value, the number of various dots formed in the pixel group is determined (step S406). The number of dots formed in the pixel group can be determined by the method described above with reference to FIGS.

The combination of the numbers of dots thus determined is converted into number data (step S40).
8). Conversion from the dot number combination to the number data is performed by referring to the correspondence table shown in FIG. Next, after storing the obtained number data in association with the multi-value quantization result value (step S410), it is determined whether or not the maximum multi-value multi-value result for the target classification number has been reached (step S410). S412). That is, as described with reference to FIG.
That is, as shown in the threshold value table of FIG. 9, a threshold number corresponding to the classification number is set in the threshold value set. Corresponding to this, the maximum value of the multi-value quantization result value is set. Is also a value corresponding to the classification number. Therefore, it is determined whether the multi-value quantization result value has reached the maximum value for the target classification number. Such a determination can be made based on the presence / absence of a threshold that does not determine the number of dots formed in the pixel group in the threshold set acquired according to the classification number. That is, if an undecided threshold value remains, it can be determined that the maximum value of the multi-value quantization result value has not been reached, and if an undecided threshold value does not remain, the maximum value of the multi-value quantization result value It can be determined that

When it is determined that the maximum value of the multi-value quantization result has not been reached (step S412: no),
After increasing the value of the multi-value quantization result RV by “1” (step S414), step S404
Returning to FIG. 5, the threshold corresponding to the new multi-value quantization result value RV is acquired from the set of thresholds, and the series of subsequent processing is repeated. When such operations are repeated and it is determined that the maximum multi-value quantization result value of the target classification number has been reached (step S412: yes), all data for that classification number is set in the conversion table.

Therefore, this time, it is determined whether or not the same processing has been performed for all classification numbers (step S416). And when the classification number which has not been processed still remains, step S4
Returning to 00, a new classification number is selected, and the above-described series of processing is performed on this classification number. When it is determined that the processing has been completed for all the classification numbers (step S416).
: Yes), since all the data of the conversion table has been set, the processing shown in FIG. 26 is terminated.

As described above, both of the threshold value table and the conversion table are the methods disclosed in Japanese Patent No. 3292104 described with reference to FIGS. 22 to 24 (the dither method is developed to form a plurality of types of dots having different sizes. It is set based on the method that makes it possible to determine whether or not there is. Therefore, if the pixel group gradation value is converted into the multi-value quantization result value with reference to the threshold value table, and the multi-value conversion result value is converted into the number data with reference to the conversion table, all the pixels in the pixel group are the same. As the image data (pixel group gradation value), the same number as the number of dots obtained by applying the method disclosed in the above patent can be obtained.

D-5. How to set the order value matrix:
Next, a method for setting the order value matrix illustrated in FIG. 14 will be described. As described above, the order value matrix is a matrix in which the order in which dots are formed is set for each pixel in the pixel group.

FIG. 27 is an explanatory diagram specifically showing a method for setting an order value matrix.
Hereinafter, description will be given with reference to the drawings. When setting the order value matrix, first, the dither matrix is divided into a plurality of blocks having the same size as the pixel group, and serial numbers are assigned to the respective blocks. As described above with reference to FIG. 19, this serial number is directly used as the pixel group classification number. FIG. 27A is an explanatory diagram conceptually showing a state in which the dither matrix is divided into a plurality of blocks. Now, assuming that the dither matrix has the size shown in FIG. 17 (that is, 128 pixels in the main scanning direction and 64 pixels in the sub-scanning direction), one pixel group has 4 pixels in the main scanning direction, Since it has a size of 2 pixels in the sub-scanning direction,
As shown in FIG. 27 (a), the dither matrix is 1024 with 32 blocks each in the main scanning direction and sub-scanning direction, with classification numbers from 1 to 1024 as a whole.
It will be divided into blocks.

When the dither matrix is divided into a plurality of blocks, one set of order value matrices is generated from each block. FIG. 27B is an explanatory diagram showing a state in which an order value matrix is generated from the block with classification number 1 as an example. In the left half of FIG. 27B, the threshold value of the dither matrix included in the block of classification number 1 is shown. FIG.
As described above using, dots are formed in order from the pixel for which a small threshold is set. Therefore, the pixel in which the first dot is formed in the first block shown in FIG. 27B can be considered as a pixel for which the threshold value “1” is set. Therefore, “1” is set as the order value for this pixel. Similarly, the pixel in which the second dot is formed can be considered as a pixel in which the threshold “42”, which is the second smallest threshold, is set. Therefore, an order value “2” is set for this pixel. In this way, if the order value “1” to the order value “8” are determined in order from the pixel with the smallest threshold set in the block, the classification numbers shown in the right half of FIG. The first order value matrix can be obtained.

The order value matrix can be set in the same manner for other classification number blocks. FIG. 27C shows that the order value “1” to the order value “8” are set in order from the pixel having a small threshold value in the block in the same way for the block with classification number 2. This shows how the order value matrix is set. The order from the classification numbers “1” to “1024” is performed by performing the above operation for all the blocks from the classification numbers “1” to “1024” shown in FIG. A value matrix can be obtained.

In the ROM built in the control circuit 260 of the color printer 200, the order value matrix set in this way is stored in advance in association with the pixel group classification number. Then, in the first dot data generation process shown in FIG. 7, the sequence value matrix stored in association with the pixel group classification number is read from the ROM to generate dot data.

D-6. Reasons for printing high-quality images:
In the first dot data generation process shown in FIG. 7, the digital camera 120 is referred to by referring to the threshold value table, conversion table, and order value matrix set as described above.
The image data received from such as is converted to dot data. If dots are formed according to the dot data thus obtained, a high-quality image can be printed. The following explains why this is possible.

First, if the technique disclosed in the above-mentioned Japanese Patent No. 3292104 is used, FIGS.
As described above using 4, the image data is converted into density data for large dots, intermediate data for medium dots, and intermediate data for small dots, and compared with the threshold value set in the dither matrix, It can be determined whether large, medium, or small dots are formed. Furthermore, if the dither matrix to be referred to at this time is a matrix in which dispersibility is considered as represented by a so-called blue noise mask or green noise mask, a high-quality image in which dots are well dispersed can be obtained. Can do.

In general, image data tends to be assigned an approximate (or the same) gradation value between adjacent pixels. In recent years, the resolution of image data tends to increase more and more due to the demand for higher image quality, but the tendency to assign an approximate or identical gradation value between adjacent pixels becomes more prominent as the resolution of the image data increases. . Therefore, as described above with reference to FIG. 24, a plurality of pixels are grouped as a pixel group, and it is determined whether each pixel in the pixel group has the same image data. Even in this case, it is rare that a difference in image quality actually occurs.

The first dot data generation process is a method for generating dot data for each pixel by paying attention to this point. In the method shown in FIG. 22 to FIG. 24, it is determined which large, medium, and small dots are formed in which pixel in the pixel group by referring to the dither matrix. On the other hand, in the first dot data generation process shown in FIG. 7, the operation of determining the pixel position where the dot is formed and the type of dot formed with reference to the dither matrix is divided into two stages. First, the number (number data) of various dots formed in the pixel group is determined, and then in which pixel in the pixel group these dots are formed. In this way, if it is determined in two steps, it is no longer necessary to refer to the dither matrix, and instead, dot data can be generated by referring to a table with a smaller amount of data. That is, it is possible to convert the pixel group gradation value into number data, and further convert the number data to generate dot data. Furthermore, in the first dot data generation process,
The pixel group tone value is not immediately converted into the number data, but once converted into a multi-value quantization result value and then converted into the number data. By doing so, it is possible to further reduce the data amount of the referenced table. Eventually, in the first dot data generation process described above, the pixel group gradation value is converted into the number data for each pixel group by referring to the threshold value table and the conversion table, and the order value matrix is obtained from the obtained number data. By determining whether or not dots are formed for each pixel with reference to FIG. 8, it is possible to obtain the same result as that obtained using the method shown in FIGS. Hereinafter, a more specific description will be given with reference to the flowchart of FIG.

First, in the first dot data generation process, a predetermined number of pixels are grouped to generate a pixel group, and a pixel group gradation value of the pixel group is determined (step S206 in FIG. 7). As described above, since image data tends to be assigned an approximate (or the same) gradation value between adjacent pixels, a plurality of pixels are grouped into a pixel group, and all the pixels in the pixel group are included. Even when handled as having the same image data, there is actually no difference in image quality.

Next, the pixel group gradation value is converted into a multi-value quantization result value with reference to the threshold value table, and the obtained multi-value quantization result value is converted into number data with reference to the conversion table (step S208 in FIG. 7). ,
S210). As is clear from the description of the setting method of the threshold value table and the conversion table, the number data obtained in this way is assumed that all the pixels in the pixel group have the same image data (pixel group tone value). The same result as that obtained when the number of various dots formed in the pixel group is determined by the method described with reference to FIGS. 22 to 24 is obtained.

After converting the number data obtained in this way into intermediate data that is easier to convert to dot data, for each pixel in the pixel group according to the order value set in the order value matrix,
The presence / absence of dot formation is determined (steps S212 and S214). As described above with reference to FIG. 24, the threshold values set in the dither matrix can be considered to represent the order in which dots are formed, and as described above with reference to FIG. The matrix is a matrix representing the order in which dots are formed at corresponding positions in the dither matrix. As for the types of dots formed in the pixel group and the number of dots, the same results as those obtained using the dither matrix have already been obtained, so the pixels in which these dots are formed according to the order value matrix If the method described with reference to FIGS. 22 to 24 is applied, it is possible to obtain the same result as when the presence or absence of dot formation for each pixel is determined. For this reason, it becomes possible to print a high-quality image in which dots are well dispersed.

Further, if the threshold value table, the conversion table, and the order value matrix are set based on a so-called blue noise characteristic or a dither matrix having a green noise characteristic, a relatively small number (8 in this embodiment) is set. This makes it possible to obtain a good dot distribution that can be realized by using a blue noise mask or a green noise mask, even though the pixel group is processed together.

In addition, in the first dot data generation process described above, the pixel group gradation value is converted into a multi-value quantization result value, the multi-value quantization result value is converted into number data, and the number data is converted into intermediate data. Finally, dot data is obtained. Eventually, four-step conversion is performed until the dot data is obtained from the pixel group gradation value. In the method described with reference to FIGS. 22 to 24, image data is converted into density data of large, medium, and small dots, and dot data is obtained from the density data. As described above, in the first dot data generation process, although multi-stage conversion is required as compared with the method shown in FIG. 22, the content of the conversion is an extremely simple process of simply referring to the table. Compared with the method shown in FIG. 22, the time required for processing does not increase, and dot data can be quickly generated to print an image.

E. Second dot data generation process:
When the color printer 200 according to the present embodiment receives image data from the digital camera 120, the color printer 200 performs the first dot data generation process described above to generate dot data. In this way, since the image data can be converted into dot data within the control circuit 260 of the color printer 200, a high-quality image can be easily printed without going through the computer 100. On the other hand, once the image data photographed by the digital camera 120 is supplied to the computer 100, it can be converted into higher resolution image data in the computer 100, or various image processing can be performed to correct the image data. it can. If image data that has been subjected to predetermined processing by the computer 100 is supplied to the color printer 200 in this way, a more preferable image can be printed.

As described above with reference to FIG. 6, the color printer 200 according to the present embodiment includes the computer 10.
When image data is received from 0, the data is received in the form of multi-value quantization result values for each pixel group, and dot data is generated by performing a second dot data generation process described below. For this reason, even a high-resolution image can be printed quickly. In the following, the outline of the second dot data generation process will be described first, and then dot data is generated by such a method so that even a high-resolution image can be quickly maintained while maintaining high image quality. The reason why printing is possible will be described.

E-1. Process overview:
FIG. 28 is a flowchart showing the flow of the second dot data generation process. When the image data is received from the computer 100 in the form of a multi-value quantization result value during the image printing process shown in FIG. 6, the CPU mounted in the control circuit 260 of the color printer 200.
Is a process executed by. That is, the image data is converted into resolution conversion processing (corresponding to step S200 in FIG. 7) and color conversion processing (step S202 in FIG. 7) in the computer 100.
The pixel group gradation value for each pixel group is obtained, and further converted to a multi-value quantization result value for each pixel group, and supplied to the color printer 200. The method of generating the multi-value quantization result value in the computer 100 can be converted by referring to the threshold value table, as in the first dot data generation process described above, but is relatively sufficient for the computer 100. Since a large-capacity memory is often installed, it is also possible to obtain a multi-value quantization result value more quickly using a method described later.

When the second dot data generation process is started, first, one pixel group to be processed is selected (step S500). Next, the multi-value quantization result value of the selected pixel group is acquired (step S502), and the classification number of the selected pixel group is calculated (step S504).

The classification number of the pixel group can be easily obtained from the position of the pixel group in the image as follows. FIG. 29 is an explanatory diagram showing a method for obtaining the classification number based on the position of the pixel group on the image. As shown in FIG. 29A, the target pixel group is an i-th pixel group in the main scanning direction and a j-th pixel group in the sub-scanning direction with reference to the upper left corner of the image. Suppose it is in position. In addition, the position of such a pixel group is represented by coordinate values (i, j). Also, the size of the dither matrix is usually not as large as the image,
As described above with reference to FIG. 20B, the dither matrix is repeatedly used while being moved in the main scanning direction.

Since one dither matrix includes 32 blocks each in the main scanning direction and the sub-scanning direction (see FIG. 19B), the position where the target pixel group is located in the dither matrix is I rows. If it is set as J row | line | column, I and J can each be calculated | required by following Formula.
I = i−int (i / 32) × 32
J = j−int (j / 32) × 32
Here, int is the above-described operator that represents rounding down to the integer. Therefore, by obtaining the values I and J by applying the above formula to the coordinate values (i, j) of the pixel group, it can be seen that the pixel group is in row I and column J in the dither matrix. From this, the classification number is
I + (J−1) × 32 (2)
Can be obtained.

Also, the values I and J representing the position of the pixel group in the dither matrix can be very simply obtained by extracting predetermined bit data from the binary display of i and j without performing the above-described calculation. Can be sought. FIG. 30 is an explanatory diagram specifically showing a method for obtaining the position of the pixel group in the dither matrix from the coordinate value (i, j) of the pixel group. FIG. 30 (a)
10-bit binary data representing the numerical value i is conceptually shown. Note that FIG.
), In order to identify each bit, serial numbers from 1 to 10 are assigned and displayed from the most significant bit to the least significant bit.

In obtaining the value I indicating the position of the pixel group, first, int (i / 32) is calculated. This calculation can be executed by shifting the binary data of i by 5 bits to the right (see FIG. 30B). Next, int (i / 32) × 32 is calculated. This calculation can be executed by bit-shifting the int (i / 32) binary data by 5 bits to the left (see FIG. 30C). Finally, by subtracting int (i / 32) × 32 from the numerical value i, the target numerical value I can be obtained. In the end, this operation is nothing but the extraction of the lower 5 bits from the binary data of the numerical value i, so that the numerical value I can be obtained very simply. Similarly, the numerical value j 2
By extracting only the lower 5 bits from the decimal data, the numerical value J can be obtained very simply. If the numerical values I and J are obtained in this way, the classification number can be calculated using the above-described equation (2). In step S504 of the second dot data generation process shown in FIG. 28, the pixel group classification number is calculated as described above.

In this way, the multi-value quantization result value of the pixel group is acquired (step S502 in FIG. 28), and the classification number is obtained (S504). By referring to the decode table, the presence or absence of dot formation is determined for each pixel in the pixel group. The represented dot data is read out (step S506). In the decode table, dot data for the pixel group is set in advance for each combination of the multi-value quantization result value of the pixel group and the classification number.

FIG. 31 is an explanatory diagram conceptually showing a decode table referred to in the second dot data generation process. As shown in the figure, in the decode table, data (dot data) representing the dot type formed in each pixel in the pixel group is set in association with the combination of the multi-value quantization result value and the classification number. ing. Accordingly, by referring to such a decoding table, corresponding dot data can be read immediately from the combination of the pixel group classification number and the pixel group gradation value. For example, if the classification number is i and the pixel group tone value is j, the dot data is DD (
i, j). The dot data read out in this way describes the presence or absence of dot formation for each pixel in the pixel group.

FIG. 32 is an explanatory diagram showing the data structure of dot data set in the decode table. As shown in FIG. 32A, dot data is 16-bit data composed of 8 sets of 2-bit data. Here, the fact that one dot data is composed of eight sets of data corresponds to the fact that eight pixels are included in one pixel group in this embodiment. Therefore, for example, when one pixel group is composed of four pixels, one dot data is composed of four sets of data. One set of data consists of 2 bits because the color printer 200 of this embodiment has one pixel per pixel.
This corresponds to the fact that four states of “large dot formation”, “medium dot formation”, “small dot formation”, “no dot formation” can be expressed. That is, 4 per pixel
If only one state can be obtained, it can be expressed by 2 bits. Therefore, a set of data corresponding to one pixel has a 2-bit data length.

Further, as shown in FIG. 32, the eight sets of data constituting the dot data are respectively associated with pixels at predetermined positions in the pixel group. For example, the first set of data at the head of the dot data shown in FIG. 32A corresponds to the pixel at the upper left corner in the pixel group, as shown in FIG. In addition, the second set of data from the top of the dot data corresponds to the second pixel from the upper left in the pixel group. Thus, the eight sets of data that make up the dot data are:
Each is associated in advance with a pixel at a predetermined position in the pixel group.

The contents of each set of data represent the types of dots formed on the corresponding pixels.
That is, the 2-bit data “11” means that a large dot is formed. The 2-bit data “10” means that a medium dot is formed, “01” means that a small dot is formed, and “00” means that a dot is not formed. As can be seen from the above description, in the dot data illustrated in FIG. 32A, a large dot is formed in the pixel at the upper left corner of the pixel group, a middle dot is formed in the third pixel from the left in the upper stage, and the lower stage. This is data indicating that a small dot is formed in the second pixel from the left, a medium dot is formed in the pixel at the lower right corner of the pixel group, and no dot is formed in the other pixels.

In this way, the data set in the decode table is data that directly represents which dot is to be formed for each pixel in the pixel group. From the combination of the classification number and the multi-value quantization result value, it is possible to immediately determine whether or not dots are formed for each pixel in the pixel group.

Next, it is determined whether or not dot formation has been determined for all the pixel groups (step S508 in FIG. 28). If there is an unprocessed pixel group (step S508: no), the process returns to step S500 and a new one is created. A pixel group is selected, and a series of processes are performed for the pixel group. If it is determined that the process has been completed for all pixel groups by repeating these operations (step S).
508: yes), the obtained dot data is output to the ink ejection head (step S).
510). Then, the second dot data generation process shown in FIG. 28 is terminated, and the process returns to the image printing process of FIG. In the image printing process, the ink ejection head is driven according to the dot data generated in this manner to eject ink droplets, thereby forming dots on the printing paper and printing the image.

E-2. Reason why multi-value conversion result value can be converted to code data:
Next, the reason why a high-quality image can be printed by the second dot data generation process described above as well as the first dot data generation process described above will be described.
FIG. 33 conceptually summarizes the general flow of processing for determining whether large, medium, and small dots are formed for each pixel in the pixel group from the multi-value quantization result value in the first dot data generation processing described above. It is explanatory drawing. As shown in the drawing, in the first dot data generation process, the number data is determined by referring to the conversion table from the multi-value quantization result value and the classification number. Also, a matrix stored in association with the classification number is read out from the sequence value matrix stored in advance. Then, using the order values set in the order value matrix and the intermediate data obtained by converting the number data, the presence or absence of dot formation for each pixel in the pixel group was determined.

As described above, in the first dot data generation process, if the multi-value quantization result value and the classification number of the pixel group are determined, the type of dot formed in each pixel in the pixel group can be determined. Therefore, if the types of dots formed in each pixel in the pixel group are obtained and stored in the decode table in advance for each combination of the multi-value quantization result value and the classification number, only the decode table is referred to. Thus, it is possible to immediately determine whether or not dots are formed. The dot data obtained in this way is exactly the same data as the dot data obtained by the first dot data generation process. Eventually, even if the multi-value quantization result value is converted into dot data with reference to the decode table, it is possible to print a high-quality image in which dots are well dispersed.

E-3. How to quickly obtain multi-valued result values in a computer:
In the first dot data generation process described above, the pixel group gradation value of the pixel group is converted into a multi-value quantization result value by referring to the threshold value table shown in FIG. But computer 1
When the pixel group gradation value is converted into the multi-value quantization result value within 00, it is possible to obtain the multi-value quantization result value more quickly. Below, this method is demonstrated easily.

FIG. 34 is an explanatory diagram conceptually showing an encode table that is referred to when the pixel group gradation value is converted into the multi-value quantization result value in the computer 100. As shown in the figure, the encoding table stores a multi-value quantization result value for each pixel group gradation value in association with each pixel group classification number. This encoding table is obtained by rewriting the threshold value table referred to in the first dot data generation process into an expression format in which the multi-value quantization result value for the pixel group gradation value is clearly shown. That is, when determining the multi-value quantization result value with reference to the threshold value table, first, as described above, the threshold value set in the classification number is read, and the number of threshold values smaller than the pixel group gradation value is read. Multi-valued result values can be obtained by counting. Therefore, if the classification number and the pixel group gradation value are determined, the multi-value quantization result value can be determined with reference to the threshold value table. Therefore, the table obtained by previously obtaining the multi-value quantization result value for each combination of the classification number and the pixel group gradation value is the encode table shown in FIG. By referring to such an encoding table, it is possible to quickly obtain a multi-value quantization result value from a combination of a classification number and a pixel group gradation value.

However, since such a decoding table has a multi-value quantization result value for each combination of a classification number and a pixel group gradation value, a large memory capacity is required to store the decoding table. There is a difficulty that. Therefore, when a relatively large memory capacity is installed, such as the computer 100, it is preferable to obtain the multi-value quantization result value by referring to the decode table. On the other hand, when the installed memory amount is relatively small, such as the color printer 200, if the multi-value quantization result value is obtained by referring to the threshold value table, the pixel with a small memory usage amount The group gradation value can be converted into a multi-value quantization result value.

As described above, according to the second dot data generation process, the decoding table is set to 1
By simply referring to the floor, it is possible to immediately determine whether or not dots are formed for each pixel in the pixel group from the multi-value quantization result value. Therefore, the multi-value quantization result value for each pixel group supplied from the computer 100 can be quickly converted into dot data.

In the computer 100, the multi-value quantization result value can be quickly obtained by referring to the decode table. Furthermore, a multi-value quantization result value for each pixel group can be expressed with a much smaller data amount than image data or dot data. Therefore, if data of an image to be printed is supplied to the color printer 200 in the form of a multi-value quantization result value, even if the image has a high resolution and therefore a large number of pixels, the data can be output quickly. Can do.

As described above, in the second dot data generation process, the multilevel halftoning result value generated quickly by the computer 100 can be quickly received and quickly converted to dot data. For this reason, a high-quality image can be printed quickly.

F. Reasons for switching the dot data generation method:
As described above, in the color printer 200 of the present embodiment, when image data is received from the digital camera 120, dot data is generated by the first dot data generation process and image data is received from the computer 100. Is received in the form of a multi-value quantization result value for each pixel group, and image data is generated by the second dot data generation processing. The reason why the dot data generation method is switched between the case of receiving image data from the digital camera 120 and the case of receiving image data from the computer 100 is as follows. .

In recent years, image data received from the computer 100 tends to have high resolution. The demand for printing images with high image quality is increasing, and along with this,
This is because, after an image is created on the computer 100, when image data is output for printing, it is often output as high-resolution data. In addition, even images taken with the digital camera 120 or the like are often output to the color printer 200 after being read into the computer 100 and after various corrections are made to the image, the resolution is increased. Yes.

When the image resolution is increased, the amount of image data increases as the number of pixels constituting the image increases. When the image data becomes large in this way, the time for converting the image data into dot data becomes longer, and in addition, the time for outputting the data to the color printer 200 becomes longer. In addition, since the time for forming dots based on the data received by the color printer 200 becomes longer, the time required for printing an image eventually increases. For this reason, when receiving image data from the computer 100, it is important to quickly convert the image data into dot data. Further, since it is necessary to supply a large amount of data from the computer 100 to the color printer 200, it is also important to supply the data in a form that can be supplied as quickly as possible.

On the other hand, when image data is directly supplied from the digital camera 120 to the color printer 200 to print an image, the process of converting the image data into dot data is performed by the color printer 2.
Must be done within 00. Generally, a CPU mounted on the color printer 200
However, the processing capacity is not as high as that installed in the computer 100, and the RAM is not equipped with a sufficient amount of RAM unlike the computer 100. Therefore, it is desirable to use a simple process that does not impose a burden on the CPU as much as possible and a process that does not compress the memory. On the other hand, when receiving image data from the computer 100, the CPU and RAM installed in the computer 100 can be used. Therefore, such a problem as when performing image processing in the color printer 200 occurs. It does not occur.

In the color printer 200 of the present embodiment, in order to satisfy both the above-described demands that occur when image data is received from the digital camera 120 for printing and when image data is received from the computer 100 for printing. The processing method for generating dot data is switched. In the following, a case where image data is received from the computer 100 will be described first, and then a case where image data is received from the digital camera 120 will be described.

F-1. When receiving image data from a computer:
First, when receiving image data from the computer 100, as described above, the data is received in the form of multi-value quantization result values for each pixel group, and converted to dot data with reference to the decode table shown in FIG. . The multi-value quantization result value for each pixel group can be expressed with a smaller amount of data than image data in which gradation values are set for each pixel or dot data representing the presence or absence of dot formation for each pixel. Is supplied in the form of a multi-value quantization result value, the image data can be quickly supplied from the computer 100 to the color printer 200.
In addition, with reference to the decode table shown in FIG. 31, the multi-value quantization result value can be quickly converted into dot data. Furthermore, by referring to the encoding table shown in FIG. 34 also inside the computer 100, the pixel group gradation value of the pixel group can be quickly converted into a multi-value quantization result value. Eventually, the multi-value quantization result value is quickly generated in the computer 100,
The obtained multi-value quantization result value is quickly supplied to the color printer 200, and further the color printer 20
Since it can be quickly converted into dot data within 0, even a high-resolution image can be printed quickly.

However, when such a method is used, it is necessary to store the encode table shown in FIG. 34 in the computer 100 and the decode table shown in FIG. 31 in the color printer 200. There is. In order to store these tables, the following memory capacity is required.

First, as shown in FIG. 34, the encoding table is stored in the encoding table because one multi-value quantization result value is set for each combination of the classification number and the pixel group gradation value. The amount of memory for this is [number of classification numbers] × [number of pixel group gradation values] × [data length of multi-value quantization result value]. The number of classification numbers is determined by the dither matrix size and the pixel group size, as described with reference to FIG. In this example, 1
Since one pixel group is composed of eight pixels and the dither matrix has a size as shown in FIG. 17, the number of classification numbers is 1024. The data length of the multi-value quantization result value is 5 bits. As described above in the description of the threshold value table setting method, if the number of dots that can be formed is three and the pixel group is composed of eight pixels, multi-value conversion is possible. This is because the number of types of result values that can be taken is at most 20, more than 32 types are not estimated, and if it is within 32 types, it can be expressed with 5 bits. Eventually, the memory capacity for storing the encoding table is 160 kbytes (= 1024 × 256 × 5 bits). As described above, since the computer 100 is equipped with a RAM having a relatively large memory capacity, even if the encoding table is stored, the memory is not compressed if the memory capacity is about this level.

Next, with respect to the decoding table, as shown in FIG. 31, one dot data of the pixel group is set for each combination of the classification number and the multi-value quantization result value, so the decoding table is stored. The amount of memory for [number of classification numbers] × [number of multi-value quantization result values] × [
Data length of dot data per pixel group]. As mentioned above, the number of classification numbers is 10
The number of 24 multi-value quantization result values is 32. The data length of dot data per pixel group is 16 bits. This is because there are three types of dots that can be formed, so if there are 2 bits per pixel, it is possible to express the presence or absence of dots formed on that pixel,
In addition, since the pixel group is composed of eight pixels, it is 2 bits × 8 pixels and 16 bits per pixel group. After all, the memory capacity to store the decode table is
64 kbytes (= 1024 × 32 × 16 bits). As described above, the amount of memory installed in the color printer 200 is not as large as that of the computer 100. However, if the memory capacity is about this level, the memory of the color printer 200 can be stored even if the decode table is stored. There is no pressure.

F-2. When receiving image data from a digital camera:
Next, when receiving image data directly from the digital camera 120, as described above,
After obtaining the pixel group gradation value for each pixel group from the image data, it is converted into a multi-value quantization result value for each pixel group with reference to the threshold value table shown in FIG. Next, referring to the conversion table shown in FIG. 11, the multi-value quantization result value is converted into number data, and this is converted into intermediate data according to the conversion table shown in FIG. Finally, the intermediate data is converted into dot data for the pixel group with reference to the order value matrix for each pixel group. If the image data is converted into dot data through multi-step conversion in this way, each conversion becomes a simple process, so the color printer 2
Even a CPU with a high processing capacity installed in 00 can perform processing promptly. In addition, since image data is not transferred from the computer 100, it does not take a long time to transfer the data and the time required for printing does not increase. In addition, since the table referred to in each conversion can be stored with a small memory capacity, the memory of the color printer 200 is not compressed. Hereinafter, this point will be specifically described.

First, with respect to the threshold value table, as shown in FIG. 9, since a set of threshold values is set for each classification number, the memory amount for storing the threshold value table is [number of classification numbers] × [
Data amount per set of threshold values]. Since the possible range of the multi-value quantization result value is at most 0 to 31, the number of threshold values included in one set of threshold values does not exceed 31, and the threshold value can be expressed by 1 byte. Therefore, after all, the memory capacity for storing the threshold value table is only 31k bytes (= 1024 × 31 × 1 bytes). Compared with the amount of memory (160 kbytes) required to store the encoding table, it can be said that the amount of memory is small.

Next, the amount of memory for storing the conversion table is as follows. As shown in FIG. 11, in the conversion table, since the number data is set for each combination of the classification number and the multi-value quantization result value, the memory amount for storing the conversion table is [classification number Number of]
× [number of multi-value quantization result values] × [data length of number data]. The number of classification numbers is 102
Since the number of 4 multi-value quantization result values is 32 and the data length of the number data is 1 byte, the memory capacity for storing the conversion table is about 32 kbytes (= 1024 × 3).
2 × 1 bytes).

The conversion table referred to when converting the number data into the intermediate data is as follows. As shown in FIG. 13, since the conversion table stores intermediate data for each piece of number data, the amount of memory required to store the conversion table is [number of pieces of number data] × [number of intermediate data]. Data length]. As described above, if there are three types of dots that can be formed and eight pixels are included in the pixel group, the number data can only take a range of 0 to 164 at most. The amount of memory for storage is only 0.3 kbytes (= 165 × 16 bits).

Finally, the memory amount for storing the order value matrix for each pixel group classification number will be described. As shown in FIG. 14, an order value is set for each pixel in the order value matrix. If the number of pixels included in the pixel group is eight, the order value can only take values from 1 to 8, and the order value can be expressed with 3 bits. Therefore, it is necessary to store one order value matrix. The memory capacity is 3 bytes (= 3 bits × 8). After all, in order to store the order value matrix for each classification number, 3 kbytes (= 1024 × 3 bits ×
The memory capacity of 8) is sufficient.

As described above, when converting image data into dot data, if the threshold value table, the conversion table, the conversion table, and the order value matrix are referred to, the threshold value table is 31 kbytes. Is 32 kbytes, the conversion table is 0.3 kbytes, the order value matrix is 3 kbytes, and only 66.3 kbytes are required in total. As described above, the amount of memory installed in the color printer 200 is not as large as that of the computer 100. However, with this memory capacity, the memory of the color printer 200 is not compressed. Therefore, even in the color printer 200 in which the processing capacity of the mounted CPU is not high as in the computer 100 and the amount of memory is limited, the image data is converted into dot data without squeezing the memory. This makes it possible to print a high-quality image relatively quickly.

G. Modified example:
In the above description, when image data is received from the digital camera 120, a multi-value quantization result value is generated by referring to the threshold value table, and then the conversion table, the conversion table, and the order value matrix are referred to. The description has been given on the assumption that the conversion result value is converted into dot data for the pixel group. As described above, the conversion table, the conversion table, and the order value matrix are 32 kbytes, 0.3 kbytes, and 3 kbytes, respectively.
Since it is only 3 kbytes, the image data could be converted to dot data without squeezing the memory of the color printer 200. However, when there is some margin in the memory of the color printer 200, the multi-value quantization result value may be converted into dot data for the pixel group with reference to the above-described decoding table. That is, when image data is received from the digital camera 120, a pixel group gradation value is obtained for each pixel group, and converted to a multi-value quantization result value with reference to a threshold value table. Then, by referring to the decoding table shown in FIG. 31, the multi-value quantization result value may be directly converted into dot data for the pixel group.

By referring to the decoding table in this way, dot data can be generated directly from the multi-value quantization result value, so that dot data can be generated quickly, and thus an image can be printed quickly. it can. Of course, as described above, a memory amount of 64 kbytes is required to store the decoding table, but it is not necessary to store the conversion table, the conversion table, and the order value matrix. Increase in memory is 28.7
k bytes.

In addition, the same decode table can be shared when the multi-value quantization result value for each pixel group is received from the computer 100 and when the image data is received from the digital camera 120. . In this case, it is possible to save a memory amount for storing the conversion table, the conversion table, and the order value matrix.

Also, various tables (threshold table, conversion table, conversion table, and order value matrix) for converting the image data received from the digital camera 120 in the color printer 200, and the multi-value quantization result value received from the computer 100. Even when a decoding table for converting the image data is stored, these tables may be compressed and stored, and a table to be referred to when generating dot data may be decompressed and used. If various tables are stored in a compressed state in this way, different tables are used depending on whether image data is received from the digital camera 120 or multivalue quantization result values are received from the computer 100. Even in this case, it is possible to prevent the memory from being compressed because different tables are stored.

Although various embodiments have been described above, the present invention is not limited to all the embodiments described above, and can be implemented in various modes without departing from the scope of the invention.
For example, in the above embodiments, the case where an image is printed by forming dots on printing paper has been described. However, the scope of application of the present invention is not limited to the case where an image is printed. For example,
The present invention can be suitably applied to a liquid crystal display device that expresses an image whose gradation changes continuously by dispersing bright spots at an appropriate density on the liquid crystal display screen.

It is explanatory drawing which showed the outline | summary of the printer as an image output device of a present Example. It is explanatory drawing which shows the structure of the computer which outputs the multi-value quantization result value for every pixel group to the color printer of a present Example. It is explanatory drawing which shows schematic structure of the color printer of a present Example. It is explanatory drawing which shows the arrangement | sequence of the inkjet nozzle in an ink discharge head. It is explanatory drawing which showed the principle which forms the dot from which a magnitude | size differs by controlling discharge of an ink drop. 3 is a flowchart illustrating a flow of image printing processing performed by the color printer of the present exemplary embodiment to print an image. It is a flowchart which shows the flow of a 1st dot data production | generation process. It is explanatory drawing which showed the method of determining the classification number of a pixel group. It is explanatory drawing which showed the threshold value table referred when multi-value-izing a pixel group gradation value. It is explanatory drawing which showed notionally that a pixel group gradation value is converted into the multi-value quantization result value according to the classification number of a pixel group. It is explanatory drawing which showed notionally the conversion table referred when converting the multi-value quantization result value of a pixel group into number data. It is explanatory drawing which showed the correspondence of the number data and the combination of the number of large dots, medium dots, and small dots. It is explanatory drawing which shows the correspondence table which matched number data and intermediate data. It is explanatory drawing which illustrated the order value matrix. It is explanatory drawing which showed a mode that the presence or absence of dot formation was determined by reading the data of the location corresponding to an order value from intermediate data. It is explanatory drawing which shows a mode that a different dot arrangement | positioning is obtained according to an order value matrix. It is explanatory drawing which expanded and illustrated a part of dither matrix. It is explanatory drawing which showed notionally the mode of determining the presence or absence of the dot formation about each pixel, referring a dither matrix. It is explanatory drawing which shows the content which the classification number for every pixel group means. It is explanatory drawing which showed the method of calculating the classification number of a pixel group. It is explanatory drawing which showed the method of calculating | requiring a classification number from the binary number display of the coordinate value of a focused pixel group. It is a flowchart which shows the flow of the halftone process which developed the dither method and made it possible to determine the presence or absence of formation of a large dot, a medium dot, and a small dot for every pixel. It is explanatory drawing which showed notionally the dot density conversion table referred when converting the gradation value of image data into the density data about each large / medium / small dot. It is explanatory drawing which showed notionally the mode that the presence or absence of formation of each large / medium / small dot was judged about each pixel in a pixel group. It is the flowchart which showed the flow of the process which sets a threshold value table. It is the flowchart which showed the flow of the process which sets a conversion table. It is explanatory drawing which showed concretely about the method of setting an order value matrix. It is a flowchart which shows the flow of a 2nd dot data production | generation process. It is explanatory drawing which showed the method of calculating | requiring a classification number based on the position of the pixel group on an image. It is explanatory drawing which showed specifically the method of calculating | requiring the position in the dither matrix of a pixel group from the coordinate value (i, j) of a pixel group. It is explanatory drawing which showed notionally the decoding table referred by the 2nd dot data generation process. It is explanatory drawing which showed the data structure of the dot data set to the decoding table. It is explanatory drawing which put together notionally the rough flow of the process which judges the formation existence of each large / medium / small dot about each pixel in a pixel group from the multi-value quantization result value in the 1st dot data generation process mentioned above. It is explanatory drawing which showed notionally the encoding table referred when converting a pixel group gradation value into a multi-value quantization result value within a computer.

Explanation of symbols

10 ... printer, 20 ... digital camera, 30 ... computer,
100: Computer 108: Peripheral device interface PIF,
109 ... disk controller DDC,
110: Network interface card NIC,
112 ... Video interface VIF,
116 ... Bus, 118 ... Hard disk, 120 ... Digital camera,
122 ... color scanner, 124 ... flexible disk,
126: Compact disc, 230: Carriage motor, 235 ... Motor,
236 ... Platen, 240 ... Carriage, 241 ... Print head,
242 ... Ink cartridge, 243 ... Ink cartridge,
244 ... Ink ejection head 260 ... Control circuit 200 ... Color printer
300 ... communication line, 310 ... storage device

Claims (12)

An image output device that outputs an image by forming dots based on dot data representing the presence or absence of dot formation for each pixel,
A first data converter that receives image data in which a gradation value for each pixel is defined, and converts the image data into the dot data;
For each pixel group in which a predetermined number of pixels are grouped together, a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received, and the multi-value quantization result value is received as the dot data A second data converter for converting into
Dot forming means for forming dots based on the dot data generated by either the first data converter or the second data converter;
The first data converter is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor Multi-value conversion means for multi-value the pixel group gradation value by comparing the tone value;
Multi-value conversion that converts the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group A conversion unit including a result value conversion unit,
The second data converter is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. An image output device, which is a conversion unit provided with dot data generation means for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data. The image output apparatus according to claim 1,
The multi-value quantization result value conversion means is
Multi-value quantization obtained for each pixel group by referring to a conversion table in which the number data representing the number of dots formed in the pixel group and the multi-value quantization result value are associated with each pixel group Number data generating means for generating the number data from the result value;
The order in which dots are formed for each pixel in the pixel group is stored for each pixel group,
Dot formation presence / absence determining means for determining the presence / absence of dot formation for each pixel in the pixel group based on the number data obtained for each pixel group and the order stored for each pixel in the pixel group And an image output device. The image output device according to claim 2,
When the number of pixels included in the pixel group is N and the number of dots formed in the pixel group is M, M continuous data that means forming dots and no dots are formed. Intermediate data generating means for generating intermediate data consisting of (N−M) continuous data meaning the number data,
The dot formation presence / absence determining means reads out data at positions corresponding to the order stored in each pixel in the pixel group from the intermediate data obtained by converting the number data of the pixel group. An image output device as means for determining the presence or absence of dot formation for each pixel group. The image output apparatus according to claim 1,
The multi-value quantization result value conversion means is obtained for each pixel group by referring to the correspondence relationship that the dot data generation means refers to when generating the dot data from the multi-value quantization result value. An image output apparatus as means for converting a multi-value quantization result value into the dot data. The image output apparatus according to claim 1,
Classifying means for assigning a classification number to each pixel group by classifying the pixel group into a plurality of types according to the position in the image,
The multi-value quantization means stores at least one threshold value for each classification number, and compares the multi-value quantization result value of the pixel group with the threshold value stored in the classification number of the pixel group. By this means, the pixel group gradation value is a multi-value means,
The multi-value quantization result value conversion means converts the multi-value quantization result value to the dot data based on the multi-value quantization result value and the classification number for the pixel group from which the multi-value quantization result value is obtained. Is a means to convert
The dot data generation means refers to the correspondence relationship in which the multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are associated with each classification number,
An image output apparatus as means for generating the dot data from the multi-value quantization result value. The image output apparatus according to claim 1,
The dot forming means is a means capable of forming a plurality of types of dots having different gradation values that can be expressed per single dot,
The multi-value quantization result value conversion means is means for converting the multi-value quantization result value into the dot data by determining whether or not to form the plurality of types of dots for each pixel in the pixel group. ,
The dot data generation means refers to a correspondence relationship in which the multi-value quantization result value and the presence / absence of formation of the plurality of types of dots in each pixel in the pixel group are associated with each pixel group. An image output device which is means for generating the dot data. An image processing apparatus that generates dot data representing the presence or absence of dot formation for each pixel by applying predetermined image processing to data representing an image, and supplies the dot data to an image output apparatus,
A first data converter that receives image data in which a gradation value for each pixel is defined, and converts the image data into the dot data;
For each pixel group in which a predetermined number of pixels are grouped together, a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received, and the multi-value quantization result value is received as the dot data A second data converter for converting into
Dot data supply means for supplying the dot data generated by either the first data conversion unit or the second data conversion unit to the image output device,
The first data converter is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor Multi-value conversion means for multi-value the pixel group gradation value by comparing the tone value;
Multi-value conversion that converts the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group A conversion unit including a result value conversion unit,
The second data converter is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. An image processing apparatus, which is a conversion unit including dot data generation means for determining whether or not to form dots for each pixel in the pixel group from values and generating the dot data. An image output method for outputting an image by forming dots based on dot data representing the presence or absence of dot formation for each pixel,
When receiving image data in which a gradation value for each pixel is defined, the step (1) of converting the image data into the dot data;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are collected, the multi-value quantization result value is Converting to the dot data (2);
And (3) forming dots based on the dot data generated by either the step (1) or the step (2),
The step (1)
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-step (1-a) for multi-value the pixel group gradation value by comparing the tone value;
A sub-step of converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( 1-b) and
The step (2)
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. An image output method comprising a sub-step (2-a) for determining whether or not to form a dot for each pixel in the pixel group from the value and generating the dot data. The image output method according to claim 8, comprising:
Sub-step (1-b)
Multi-value quantization obtained for each pixel group by referring to a conversion table in which the number data representing the number of dots formed in the pixel group and the multi-value quantization result value are associated with each pixel group Generating the number data from the result value;
The order in which dots are formed for each pixel in the pixel group is stored for each pixel group,
Determining the presence or absence of dot formation for each pixel in the pixel group based on the number data obtained for each pixel group and the order stored for each pixel in the pixel group;
An image output method which is a process comprising: An image processing method for generating dot data representing the presence or absence of dot formation for each pixel by applying predetermined image processing to data representing an image, and supplying the dot data to an image output device,
When receiving image data in which a gradation value for each pixel is defined, the step (A) of converting the image data into the dot data;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are collected, the multi-value quantization result value is A step (B) of converting into the dot data;
And (C) supplying the dot data generated by either the step (A) or the step (B) to the image output device,
The step (A)
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-process (Aa) that multi-values the pixel group gradation value by comparing the tone value;
A sub-step of converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( A-b) and
The step (B)
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. An image processing method comprising a sub-step (Ba) for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data. A program for realizing a method of outputting an image by forming a dot on the basis of dot data representing the presence or absence of dot formation for each pixel by a computer,
A function (1) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are collected, the multi-value quantization result value is A function (2) for converting to the dot data;
A function (3) for forming dots based on the dot data generated by either the function (1) or the function (2) is realized using a computer,
The function (1) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (1-a) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( 1-b) and a function having
The function (2) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. A program having a sub-function (2-a) for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data. A computer program for realizing a method of generating dot data representing the presence or absence of dot formation for each pixel and supplying it to an image output device by performing predetermined image processing on the data representing the image. And
A function (A) for converting the image data into the dot data when image data in which a gradation value for each pixel is defined is received;
When a multi-value quantization result value of a pixel group gradation value that is a gradation value representing the pixel group is received for each pixel group in which a predetermined number of pixels are grouped, the multi-value quantization result value is A function (B) for converting to the dot data;
A function (C) for supplying the dot data generated by either the function (A) or the function (B) to the image output device is realized using a computer,
The function (A) is
When the image data is received, the pixel group gradation value is determined from the gradation value of each pixel collected in the pixel group, and at least one threshold value stored in each pixel group and the pixel group floor A sub-function (Aa) that multi-values the pixel group gradation value by comparing the tone value;
A sub-function for converting the multi-value quantization result value into the dot data by determining the presence or absence of dot formation for each pixel in the pixel group based on the multi-value quantization result value obtained for each pixel group ( A-b) and
The function (B) is
The multi-value quantization result value and the presence or absence of dot formation for each pixel in the pixel group are referred to the correspondence relationship associated with each pixel group, and the multi-value quantization result received for each pixel group. A program having a sub-function (Ba) for determining whether or not to form dots for each pixel in the pixel group from the values and generating the dot data.

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