JP2009077431A - Image processing apparatus, and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To uniformly deal with a feature amount of an image regardless of a difference in a color space. <P>SOLUTION: Image data and color space conversion information are received, and a color space of the image data is converted into a standard color space, wherein the color space conversion information is information for converting the color space of the image data into the standard color space and the standard color space is a color space preset as a standard. Next, the image data in the standard color space are analyzed to extract a prescribed feature amount from images. Otherwise, the feature amount may also be extracted first and then converted into a feature amount of the standard color space in accordance with the color space conversion information. Thus, since the feature amount of the standard color space can be extracted regardless of the color space of the image data, it becomes possible to uniformly deal with various image data on the basis of the feature amount. As a result, processing for correcting or retrieving image data on the basis of the feature amount, for example, can be appropriately and easily performed. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a technique for analyzing image data and extracting a feature amount of an image.

Due to advances in digital technology such as computers, today, images are often handled as digitized image data. If the image is expressed in the form of image data, the image can be taken into a computer and various corrections can be made, or the image data can be output to a printing apparatus for printing. Such image data can be generated using various application programs running on a computer, but various image devices that generate image data such as scanners and digital cameras have been developed.
Supplied to the market.

In addition, when correcting image data, it is performed to analyze the image data, extract the feature amount of the image, and perform correction according to the extracted feature amount (for example, Patent Document 1, Patent Document). 2). As the image feature amount, for example, various values such as a minimum gradation value, a maximum gradation value, and an average value of gradation values are used. Since the image feature amount is obtained by analyzing the image data, the obtained feature amount value depends on the color space of the image data.

JP-A-5-63972 JP 9-233336 A

However, in recent years, in order to make it possible to generate high-quality image data by making full use of the performance of various image devices that generate image data, it is unique to each device set according to the characteristics of the image device. Color space tends to be used. Since image feature values can be obtained by analyzing image data, if the image data is described in a color space specific to the device, the obtained feature value values will also be different, so the feature values are extracted. However, there is a problem in that it cannot be used across various image data.

The present invention has been made to solve the above-described problems in the prior art,
An object of the present invention is to provide a technique for extracting feature data in a state where it can be used across a cross-section even for image data described in different color spaces.

In order to solve at least a part of the problems described above, the first image data analysis apparatus of the present invention employs the following configuration. That is, an image data analysis apparatus that extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data, and the image data of the image to be extracted A color space conversion information acquisition unit for acquiring color space conversion information for converting the received image data into image data of a standard color space which is a color space set in advance as a standard; The received image data is converted into image data in the standard color space based on the color space conversion information, and the predetermined data by analyzing the image data converted into the standard color space. And a feature amount extracting means for extracting the feature amount.

The first image data analysis method of the present invention corresponding to the above image data analysis apparatus extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data. A first step of receiving image data of an image from which the feature amount is to be extracted, and an image of a standard color space that is a color space set as a standard in advance. A second step of acquiring color space conversion information for conversion into data, and a third step of converting the received image data into image data of the standard color space based on the color space conversion information; And a fourth step of extracting the predetermined feature amount by analyzing the image data converted into the standard color space.

In the first image data analysis apparatus and the first image data analysis method of the present invention, when the image data and the color space conversion information are received, the image data is preset as a standard based on the color space conversion information. The image data is converted into image data in a standard color space as a color space. here,
The color space conversion information is information for converting color space data of image data into standard color space data, and can take various forms such as a conversion formula or a conversion matrix. As the standard color space, any color space can be used as long as it has a sufficiently wide color gamut and is widely used as a standard. Next, a predetermined feature amount is extracted from the image by analyzing the image data converted into the standard color space.

In this way, the feature quantity of the standard color space can be extracted regardless of the color space in which the image data is described. For this reason, since a large number of image data can be handled in a unified manner based on the feature amount beyond the difference in the color space describing the image data, for example, a process for correcting the image data based on the feature amount Alternatively, it is possible to appropriately and easily perform processing for retrieving image data.

In order to solve at least a part of the problems described above, the second image data analysis apparatus of the present invention employs the following configuration. That is, an image data analysis apparatus that extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
Image data receiving means for receiving image data of an image from which the feature amount is to be extracted, and data in a color space in which the image data is described are converted into data in a standard color space which is a color space set as a standard in advance. A color space conversion information acquisition unit that acquires color space conversion information for the image data; a feature amount extraction unit that extracts the predetermined feature amount by analyzing the received image data; and It is characterized by comprising a feature value conversion means for converting into a feature value in the standard color space by converting based on the space conversion information.

The second image data analysis method of the present invention corresponding to the above-described image data analysis apparatus extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data. A method (A) of receiving image data of an image from which the feature amount is to be extracted, and a color space in which a color space in which the image data is described is set in advance as a standard A step (B) for obtaining color space conversion information for conversion into data of a standard color space, a step (C) for extracting the predetermined feature amount by analyzing the received image data, The gist of the present invention is to provide a step (D) of converting the extracted feature quantity based on the color space conversion information into a feature quantity in the standard color space.

In the second image data analysis apparatus and the second image data analysis method of the present invention, when image data and color space conversion information are received, the image data is first analyzed to extract image feature amounts. Next, the extracted feature amount is converted into a feature amount of the standard color space based on the color space conversion information.

Even in this way, the feature quantity in the standard color space can be extracted regardless of the color space of the image data, so that a large number of image data can be handled in a unified manner based on the feature quantity. Thus, it is possible to appropriately and easily perform processing for correcting image data based on the above, processing for searching for image data, and the like.

In the first image data analysis device or the second image data analysis device described above, a so-called colorimetric color space is set as the standard color space, and the color space of the image data is converted to the colorimetric color space. This information may be acquired as color space conversion information.

The colorimetric color space including the L * a * b * color space has an infinitely wide color gamut in principle.
In addition, since it is widely used as a standard color section, it is preferable to set a colorimetric color space as a standard color space because the extracted feature amount can be used more widely.

Further, the above-described image data analysis apparatus and image data analysis method of the present invention can be grasped as a form of generating meta image data by adding the extracted feature amount to the image data as metadata. . That is, the first meta image data generation device of the present invention corresponding to the first image data analysis device described above adds meta data indicating information about the image to the image data representing the image, thereby adding the meta data. A meta image data generating device for generating meta image data as image data accompanied by data, wherein the image data receiving means receives the image data, and the received image data is a standard color as a color space set as a standard in advance. Color space conversion information acquisition means for acquiring color space conversion information for conversion to space image data, and the received image data is converted to image data of the standard color space based on the color space conversion information. Feature data extraction means for extracting the predetermined feature data by analyzing the image data converted into the standard color space And stage, a feature quantity the extracted, by adding as the metadata to the image data received above and summarized in that and a metadata adding unit which generates the meta image data.

The first meta image data generation method of the present invention corresponding to the above-described meta image data generation apparatus adds metadata indicating information about an image to image data representing the image, thereby adding the metadata. A meta image data generation method for generating meta image data as accompanying image data, the step (1) of receiving the image data, and the received image data,
Step (2) of acquiring color space conversion information for converting into image data of a standard color space which is a color space set as a standard in advance, and the received image data based on the color space conversion information A step (3) of converting the image data into a standard color space, a step (4) of extracting the predetermined feature amount by analyzing the image data converted into the standard color space, and the extracted feature amount. Is added to the received image data as the metadata, thereby generating the meta image data (5).

In addition, the second meta image data generation device of the present invention corresponding to the second image data analysis device described above adds meta data indicating information about the image to the image data representing the image. A meta image data generating device for generating meta image data as image data accompanied by data, wherein image data receiving means for receiving the image data and data of a color space in which the image data is described are set in advance as a standard. A color space conversion information acquisition means for acquiring color space conversion information for conversion into data of a standard color space, which is a color space, and a feature amount for extracting the predetermined feature amount by analyzing the received image data An extraction unit; and a feature amount conversion for converting the extracted feature amount into a feature amount in the standard color space by converting the extracted feature amount based on the color space conversion information. And stage, the converted feature quantities by adding as the metadata to the image data received above and summarized in that and a metadata adding unit which generates the meta image data.

Furthermore, in the second meta image data generation method of the present invention corresponding to the above-described meta image data generation apparatus, metadata indicating information about the image is added to the image data representing the image, thereby adding the metadata. A meta image data generation method for generating meta image data as accompanying image data, the step (a) of receiving the image data, and a color space data in which the image data is described as a color set in advance as a standard A step (a) of obtaining color space conversion information for conversion into data of a standard color space which is a space, a step (c) of extracting the predetermined feature amount by analyzing the received image data, Converting the extracted feature quantity into a feature quantity in the standard color space by converting the extracted feature quantity based on the color space conversion information (D)
And a step (e) of generating the meta image data by adding the converted feature quantity as the metadata to the received image data.

The meta image data generated by the meta image data generating apparatus and the meta image data generating method of the present invention has an image feature amount added as metadata, and this feature amount is set in advance as a standard. It is a feature quantity in the standard color space that is a color space.
That is, even if the color space of the image data is different, the feature amount added as metadata can be handled in a unified manner, so that the processing for correcting the image data based on the feature amount or the feature amount It is possible to appropriately and easily perform various processes using the feature amount, such as a process of searching for image data based on the image 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 data analysis method or image data generation method and to execute a predetermined function. Accordingly, the present invention provides the following program,
Or the aspect as a recording medium which recorded this program is also included. That is, the program of the present invention corresponding to the first image data analysis method described above is a method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data. ,
A program implemented using a computer, the first function for receiving image data of an image from which the feature amount is to be extracted, and a standard that is a color space in which the received image data is set in advance as a standard A second function for acquiring color space conversion information for conversion to image data in a color space; and a second function for converting the received image data into image data in the standard color space based on the color space conversion information. The gist of the present invention is to realize the third function and the fourth function for extracting the predetermined feature amount by analyzing the image data converted into the standard color space using a computer.

Further, the recording medium of the present invention corresponding to the above program can read a program for extracting a predetermined feature amount from an image represented by the image data by performing a predetermined image analysis on the image data. A first function for receiving image data of an image from which the feature amount is to be extracted, and an image in a standard color space which is a color space set as a standard in advance. A second function of acquiring color space conversion information for conversion into data, and a third function of converting the received image data into image data of the standard color space based on the color space conversion information; And recording a program for realizing, using a computer, a fourth function for extracting the predetermined feature amount by analyzing the image data converted into the standard color space It is summarized as is.

The program of the present invention corresponding to the second image data analysis method described above is a method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data. A program for realizing using a computer, the function (A) for receiving image data of an image from which the feature amount is to be extracted, and data of a color space in which the image data is described as a standard in advance A function (B) for obtaining color space conversion information for conversion to data in a standard color space, which is a set color space, and a function for extracting the predetermined feature amount by analyzing the received image data ( C) and a function for converting the extracted feature quantity into a feature quantity in the standard color space by converting the feature quantity based on the color space conversion information (
It is a gist to realize D) using a computer.

Further, the recording medium of the present invention corresponding to the above program can read a program for extracting a predetermined feature amount from an image represented by the image data by performing a predetermined image analysis on the image data. A color space preset as a standard with a function (A) for receiving image data of an image from which the feature amount is to be extracted and data of a color space in which the image data is described. A function (B) for obtaining color space conversion information for conversion into data of a standard color space, a function (C) for extracting the predetermined feature amount by analyzing the received image data, A program that realizes the function (D) for converting the extracted feature quantity based on the color space conversion information into the feature quantity in the standard color space using a computer. And summarized in that that records.

Further, the program of the present invention corresponding to the first image data generation method described above adds metadata indicating information about the image to the image data representing the image, so that the metadata as the image data accompanied by the metadata is added. A program for realizing a method of generating image data using a computer, the function (1) for receiving the image data, and a standard color as a color space in which the received image data is set in advance as a standard A function (2) for acquiring color space conversion information for conversion into image data of space, and a function of converting the received image data into image data of the standard color space based on the color space conversion information ( 3), a function (4) for extracting the predetermined feature amount by analyzing the image data converted into the standard color space, and the extracted feature And by adding as said metadata to said received image data, and summarized in that realized using a computer function and (5) for generating the meta image data.

Also, the recording medium of the present invention corresponding to the above program generates meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing the image. A recording medium in which a program is recorded so as to be readable by a computer, the function (1) for receiving the image data, and the received image data,
A function (2) for acquiring color space conversion information for converting into image data of a standard color space which is a color space set as a standard in advance, and the received image data based on the color space conversion information A function (3) for converting the image data into the standard color space, a function (4) for extracting the predetermined feature amount by analyzing the image data converted into the standard color space, and the extracted feature amount Is added to the received image data as the metadata to record a program for realizing the function (5) for generating the meta image data using a computer.

Furthermore, the program of the present invention corresponding to the second image data generation method described above adds metadata indicating information about the image to the image data representing the image, whereby the metadata as the image data accompanied by the metadata is added. A program for realizing a method of generating image data by using a computer, wherein the function (a) for receiving the image data and the data of the color space in which the image data is described are preset as a standard. A function (a) for obtaining color space conversion information for conversion into data of a standard color space, which is a color space, and a function (c) for extracting the predetermined feature amount by analyzing the received image data A function (d) for converting the extracted feature quantity into a feature quantity in the standard color space by converting the extracted feature quantity based on the color space conversion information; and the conversion The feature amount, by adding as the metadata to the image data received above and summarized in that realized using a computer function and (e) generating the meta image data.

Also, the recording medium of the present invention corresponding to the above program generates meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing the image. A recording medium in which a program is recorded so as to be readable by a computer, the function (a) for receiving the image data, and the color space data in which the image data is described as a standard color space set as a standard. A function (a) for acquiring color space conversion information for conversion into data of color space, a function (c) for extracting the predetermined feature amount by analyzing the received image data, and the extracted A function (d) for converting the feature quantity into the feature quantity in the standard color space by converting the feature quantity based on the color space conversion information.
And a program for realizing the function (e) for generating the meta image data by adding the converted feature amount as the metadata to the received image data. This is the gist.

If these programs are read into a computer and the various functions described above are realized, the image feature values can be handled uniformly without being affected by the color space of the image data. Make appropriate corrections, search for appropriate image data, etc.
The image data can be used in various ways.

Hereinafter, in order to clarify the contents of the present invention described above, examples will be described in the following order.
A. Summary of Examples:
B. Device configuration:
B-1. overall structure:
B-2. Internal configuration:
B-2-1. Internal configuration of the scanner unit:
B-2-2. Internal configuration of the printer unit:
C. Overview of image printing process:
D. Overview of image formation processing:
E. Feature amount extraction processing of the first embodiment:
F. Feature amount extraction processing of the second embodiment:
G. 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 outline of the image data analysis apparatus 1 of the present embodiment. The illustrated image data analysis apparatus 1 receives image data from various image devices such as the digital camera 20, the computer 30, and the scanner 40, and analyzes the image data to extract image feature amounts. As the image feature amount, for example, various values such as a minimum gradation value, a maximum gradation value, an average value of gradation values, a standard deviation, and a gradation value histogram can be extracted. The feature amount obtained in this way is added to, for example, a header portion of the image data, and supplied as meta image data to an image output device (for example, the printer 2) or stored in the image server 3. When the image output device such as the printer 2 receives the meta image data to which the feature amount is added, it is possible to print a more preferable image by correcting the image data according to the feature amount. Further, the image server 3 can quickly find desired image data from a vast amount of image data by searching for an image based on the feature amount.

However, in recent years, in order to obtain a higher quality image, the image device such as the digital camera 20 or the scanner 40 tends to use a unique color space according to the characteristics of the device. Since image feature values are obtained by analyzing image data, if image data is represented in a unique color space for each device, the resulting feature value values will also differ, resulting in feature values. Correct the image appropriately based on or from a huge amount of image data,
There arises a problem that desired image data cannot be searched based on the feature amount. In view of these points, the image data analysis apparatus 1 of the present embodiment extracts image feature amounts as follows.

First, image data from an image device such as the digital camera 20, the computer 30, or the scanner 40 is received by an image data receiving module, and then supplied to the image analysis module, and feature amounts are extracted in the image analysis module. Here, the “module” is a series of processes performed internally by the image data analysis apparatus 1 in order to extract feature amounts, with a focus on functions. Therefore, a “module” can be realized as a part of a program, or can be realized by using a logic circuit having a specific function, or can be realized by combining them. is there.

In addition to the reception of the image data, the color space conversion information acquisition module acquires color space conversion information from the image equipment such as the digital camera 20, the computer 30, and the scanner 40. Here, the color space conversion information is information for converting color space data describing image data into data of a color space (standard color space) set as a standard in advance. The color space conversion information can be received in the form of a conversion formula or in the form of a so-called color profile. In addition, as the standard color space, any color space can be used as long as it has a sufficiently wide color gamut and is a standard color space, but L * a * A so-called colorimetric color space represented by the b * color space is particularly suitable because it has an infinitely wide color gamut in principle.

In the image analysis module, a feature amount extraction module, a data conversion module, and the like are provided. Among these, the feature amount extraction module analyzes the image data and extracts the feature amount of the image, and the data conversion module converts the color space data describing the image data into the standard color based on the color space conversion information. Performs processing to convert to spatial data.

Various modes can be taken as the mode for extracting the feature amount in the image analysis module. For example, the image data supplied from the image data receiving module is converted into image data in the standard color space by the data conversion module. Next, the feature amount extraction module can extract the feature amount by analyzing the converted image data. In this way, if the image data is converted into image data in the standard color space in advance by the data conversion module, even if the image data is image data described in a color space unique to the image device, the standard color It is possible to extract the feature amount of the space. Alternatively, the image data supplied from the image data receiving module may be analyzed to extract a feature value, and the obtained feature value may be converted into a standard color space feature value by the data conversion module. Even in this case, the feature amount of the standard color space can be finally obtained.

In the meta image data generation module, the feature quantity of the standard color space obtained in this way is
By adding to the image data received from the image data receiving module, meta image data is generated and then output to an image output device such as the printer 2 or the image server 3. In this way, the feature amount is the feature amount of the standard color space, regardless of the color space in which the image data received from the digital camera 20 or the computer 30 is described. For this reason, it is possible to appropriately correct the image data based on the feature amount, or to quickly find out desired image data from the enormous amount of image data based on the feature amount.

FIG. 1 illustrates the case where the feature amount is added to the image data and is output as meta image data. However, the feature amount is not necessarily output in the form of meta image data, and the feature amount and the image data are not necessarily output. May be output separately. In FIG. 1, the image data analysis apparatus 1 is displayed as being provided separately from an image device such as the digital camera 20, the printer 2, and the image server 3. 1 may be incorporated in the digital camera 20, the printer 2, the image server 3, or the like. Hereinafter, such an image data analyzing apparatus 1 will be described in detail based on examples.

B. Device configuration:
B-1. overall structure:
FIG. 2 is a perspective view showing the external shape of the printing apparatus 10 in which the image data analysis apparatus of this embodiment is incorporated. As illustrated, the printing apparatus 10 includes a scanner unit 100 and a printer unit 2.
00 and an operation panel 3 for setting operations of the scanner unit 100 and the printer unit 200
00 or the like. The scanner unit 100 has a scanner function of reading a printed image and generating image data, and the printer unit 200 has a printer function of receiving image data and printing an image on a print medium. . Further, if an image (original image) read by the scanner unit 100 is output from the printer unit 200, a copy function can be realized. That is, the printing apparatus 10 of this embodiment is a so-called scanner / printer / copy combined apparatus (hereinafter, referred to as “scanner / printer / copier combined apparatus”).
It is called SPC composite device).

FIG. 3 shows a document table cover 1 provided at the top of the printing apparatus 10 for reading a document image.
It is explanatory drawing which shows a mode that 02 was opened. As shown in the drawing, when the document table cover 102 is opened upward, a transparent document table glass 104 is provided, and various mechanisms to be described later for realizing the scanner function are mounted therein. . When reading a document image, as shown in the figure, the document table cover 102 is opened and the document image is placed on the document table glass 104.
The button on the operation panel 300 is operated after the document table cover 102 is closed. This way
It is possible to immediately convert a document image into image data.

The scanner unit 100 is entirely housed in an integrated case, and the scanner unit 100 and the printer unit 200 are provided with a hinge mechanism 204 (FIG. 4) on the back side of the printing apparatus 10.
Reference). For this reason, by lifting the front side of the scanner unit 100, it is possible to rotate only the scanner unit 100 at the hinge portion.

FIG. 4 is a perspective view illustrating a state in which the front side of the scanner unit 100 is lifted and rotated. As shown in the figure, in the printing apparatus 10 of the present embodiment, the upper surface of the printer unit 200 can be exposed by lifting the front side of the scanner unit 100. Inside the printer unit 200, various mechanisms to be described later for realizing the printer function, a control circuit 260 to be described later for controlling the operation of the entire printing apparatus 10 including the scanner unit 100, and the scanner unit 100 are further described. And a power supply circuit (not shown) for supplying power to the printer unit 200 and the like. Also, as shown in FIG. 4, an opening 202 is provided on the upper surface of the printer unit 200, and replacement of consumables such as ink cartridges, paper jam handling, and other minor repairs are performed. Can be performed easily.

B-2. Internal configuration:
FIG. 5 is an explanatory diagram conceptually showing the internal configuration of the printing apparatus 10 of this embodiment. As described above, the printing apparatus 10 includes the scanner unit 100 and the printer unit 200, and various configurations for realizing the scanner function are mounted in the scanner unit 100. Is equipped with various configurations for realizing the printer function. Hereinafter, the internal configuration of the scanner unit 100 will be described first, and then the internal configuration of the printer unit 200 will be described.

B-2-1. Internal configuration of the scanner unit:
The scanner unit 100 includes a transparent platen glass 104 on which a document image is set, a document platen cover 102 for holding the set document image, a reading carriage 110 for reading the set document image, and a reading carriage 110. The driving belt 120 is configured to move in the reading direction (main scanning direction), the driving motor 122 supplies power to the driving belt 120, the guide shaft 106 that guides the movement of the reading carriage 110, and the like. The operations of the drive motor 122 and the reading carriage 110 are controlled by a control circuit 260 described later.

When the drive motor 122 is rotated under the control of the control circuit 260, the movement is transmitted to the reading carriage 110 via the driving belt 120. As a result, the reading carriage 110 is
While being guided by the guide shaft 106, it moves in the reading direction (main scanning direction) according to the rotation angle of the drive motor 122. Further, the drive belt 120 is constantly adjusted to be in a moderately tensioned state by the idler pulley 124. Therefore, if the drive motor 122 is rotated in the reverse direction, the reading carriage 110 is moved in the reverse direction by a distance corresponding to the rotation angle. It is also possible to make it.

Inside the reading carriage 110 are a light source 112, a lens 114, a mirror 116, and a CC.
A D sensor 118 and the like are mounted. Light from the light source 112 is applied to the platen glass 104 and reflected by a document image set on the platen glass 104. The reflected light is guided to the lens 114 by the mirror 116, collected by the lens 114, and detected by the CCD sensor 118. The CCD sensor 118 includes a linear sensor in which photodiodes that convert light intensity into an electrical signal are arranged in a row in a direction orthogonal to the moving direction (main scanning direction) of the reading carriage 110. Therefore, by moving the reading carriage 110 in the main scanning direction and irradiating the original image with light from the light source 112 and detecting the reflected light intensity by the CCD 118, an electrical signal corresponding to the original image can be obtained.

Further, the light source 112 is composed of light emitting diodes of three colors of RGB, and can sequentially irradiate light of R color, G color, and B color at a predetermined cycle. C
In CD118, the reflected light of R color, G color, and B color is detected sequentially. In general, the red portion of the image reflects R light, but hardly reflects G or B light, so the R reflected light represents the R component of the image. Similarly, the reflected light of G color represents the G component of the image, and the reflected light of B color represents the B component of the image. Accordingly, if the original image is irradiated while switching the light of three colors of RGB at a predetermined cycle and the reflected light intensity is detected by the CCD 118 in synchronization therewith, the R component, G component and B component of the original image can be detected. It is possible to read a color image. Note that since the reading carriage 110 is moved even while the color of the light emitted by the light source 112 is switched, the position of the image for detecting each component of RGB corresponds to the movement amount of the reading carriage 110 strictly. The difference is as much as
After reading each component, it can be corrected by image processing.

B-2-2. Internal configuration of the printer unit:
Next, the internal configuration of the printer unit 200 will be described. The printer unit 200 includes a control circuit 260 that controls the overall operation of the printing apparatus 10, a print carriage 240 that prints an image on a print medium, a mechanism that moves the print carriage 240 in the main scanning direction, and printing. A mechanism for feeding media is mounted.

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

The mechanism that moves the print carriage 240 in the main scanning direction includes a carriage belt 231 for driving the print carriage 240, a carriage motor 230 that supplies power to the carriage belt 231, and an appropriate tension is constantly applied to the carriage belt 231. Tension pulley 232 for holding the carriage, and carriage guide 233 for guiding the movement of the print carriage 240
And an origin position sensor 234 for detecting the origin position of the print carriage 240. When the carriage motor 230 is rotated under the control of the control circuit 260 described later,
The print carriage 240 can be moved in the main scanning direction by a distance corresponding to the rotation angle. Further, if the carriage motor 230 is rotated in the reverse direction, the print carriage 240 can be moved in the reverse direction.

The mechanism for feeding the print medium includes a platen 236 that supports the print medium from the back side, a paper feed motor 235 that feeds the paper by rotating the platen 236, and the like. By rotating the paper feed motor 235 under the control of the control circuit 260 described later, the print medium can be fed in the sub-scanning direction by a distance corresponding to the rotation angle.

The control circuit 260 has a CPU, a ROM, a RAM, a D / A converter that converts digital data into an analog signal, and a peripheral device interface PIF for exchanging data with peripheral devices. It is composed of The control circuit 260 controls the overall operation of the printing apparatus 10, and controls these operations while exchanging data with the light source 112, the drive motor 122, and the CCD 118 mounted on the scanner unit 100.
The control circuit 260 also performs processing for analyzing image data and extracting feature amounts, and processing for correcting image data according to feature amounts.

In addition, the control circuit 260 is used to form an image on the print medium.
While driving the 0 and paper feed motors 235 to perform main scanning and sub-scanning of the print carriage 240, control is also performed to supply drive signals to the ink discharge heads 244 to 247 of each color to discharge ink droplets. The drive signals supplied to the ink ejection heads 244 to 247 are generated by reading image data from the computer 30, the digital camera 30, the external storage device 32, etc., and performing image processing to be described later. Of course, the scanner unit 10
It is also possible to generate a drive signal by performing image processing on the image data read at 0. In this way, under the control of the control circuit 260, the ink droplets are ejected from the ink ejection heads 244 to 247 to form the ink dots of the respective colors on the printing medium while the print carriage 240 is moved in the main scan and the sub scan. An image can be formed. Of course, a series of image processing for forming an image is not performed in the control circuit 260, but data subjected to image processing in advance is received from the computer 30 or the like, and the main scanning and printing of the print carriage 240 are performed according to this data. It is also possible to drive the ink discharge heads 244 to 247 while performing sub-scanning.

The control circuit 260 is also connected to the operation panel 300 so as to be able to exchange data. By operating various buttons provided on the operation panel 300, detailed operation modes of the scanner function and the printer function are set. It is possible to set. Further, it is possible to set a detailed operation mode from the computer 30 via the peripheral device interface PIF.

FIG. 6 is an explanatory diagram showing a state in which a plurality of nozzles Nz for ejecting ink droplets are formed on the ink ejection heads 244 to 247 of each color. As shown in the figure, four sets of nozzle arrays for ejecting ink droplets of each color are formed on the bottom surface of each color ink ejection head, and 48 nozzles Nz are arranged in a nozzle pitch k in one set of nozzle arrays. They are arranged in a zigzag pattern with an interval of. A drive signal is supplied from the control circuit 260 to each of these nozzles Nz, and each nozzle Nz discharges an ink droplet of each ink according to the drive signal.

Various methods can be applied to the method of ejecting ink droplets from the ink ejection head. That is, a method of ejecting ink 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. Also, instead of ejecting ink, use a method that forms ink dots on printing paper using phenomena such as thermal transfer, or a method that attaches toner powder of each color onto the printing medium using static electricity. Is also possible.

In the printing apparatus 10 described above, image data is received from the digital camera 20 or the like,
Alternatively, when the scanner unit 100 reads an original image and generates image data, the control circuit 2
After extracting the feature amount of the image at 60, the image is printed with correction according to the feature amount. Also,
When extracting feature quantities, the image data is extracted in a form that does not depend on the color space of the image data. Therefore, even if the image data is described in any color space, appropriate correction is performed according to the feature quantities. It is possible to do. In the following, a process of receiving image data and printing an image (image printing process) will be briefly described, and then a process of extracting an image feature amount (a feature amount extraction process) in the image printing process will be described in detail. .

C. Image printing process:
FIG. 7 is a flowchart illustrating a flow of image printing processing performed for printing an image by the printing apparatus 10 according to the present exemplary embodiment. Such processing is performed by the control circuit 2 installed in the printing apparatus 10.
Reference numeral 60 denotes processing executed using functions such as a built-in CPU, RAM, and ROM.

When printing an image, first, a process of reading image data of an image to be printed is performed (step S100). As the image data, image data taken by the digital camera 20, image data created by various application programs operating on the computer 30, or image data read by the scanner unit 100 can be used. In this embodiment, these image data are all RGB image data expressed by gradation values of R, G, and B colors. However, the RGB image data also includes the sRGB color space. There are various color space standards. Therefore, when reading the image data, in addition to the RGB image data, information for converting the color space of the RGB image data into a colorimetric color space (L * a * b * color space) is also acquired. In this embodiment, RG
Although the description will be made assuming that the color space of the B image data is converted to the colorimetric color space, actually, if the color space has a sufficiently wide color gamut and is widely used as a standard, the color space is measured. Any color space can be used in addition to the color space.

Next, a process of extracting a predetermined feature amount from the image is performed by analyzing the read image data (step S102). The details of the feature amount extraction processing will be described in detail later, but processing for extracting the feature amount of the colorimetric color space is performed regardless of the color space in which the image data is described.

Based on the extracted feature quantity, the image data received from the digital camera 20 or the computer 30 is corrected (step S104). Since various methods are known for correcting image data based on feature amounts, a description thereof is omitted here. In this embodiment, the colorimetric color space is not related to the color space of the image data. Features are obtained. For this reason, since all image data can be handled uniformly according to the same standard, it is possible to correct appropriately.

An image can be formed on the print medium by performing an image forming process as described below on the image data thus corrected (step S106).

D. Overview of image formation processing:
FIG. 8 is a flowchart illustrating a flow of image forming processing for forming an image using ink dots on a print medium. Such a process is a process executed by the control circuit 260 on the image data corrected according to the feature amount in the above-described image printing process.

When the image forming process is started, the control circuit 260 first performs a process of converting the resolution of the image data into a resolution (printing resolution) for printing by the printer unit 200 (step S150). When the resolution of the image data is lower than the print resolution, the image data is converted to a higher resolution by performing interpolation calculation between adjacent pixels and setting new image data. vice versa,
When the resolution of the image data is higher than the print resolution, the image data is converted to a lower resolution by thinning out the image data at a certain rate from between adjacent pixels. In the resolution conversion process, a process of converting the resolution of the image data to the print resolution is performed by generating or thinning out the image data at an appropriate ratio with respect to the image data.

After the resolution of the image data is converted to the printing resolution in this way, color conversion processing is subsequently performed (
Step S152). Here, the color conversion process is a process of converting RGB image data expressed by R, G, B colors into image data expressed by gradation values of C, M, Y, K colors. The color conversion process is performed by referring to a three-dimensional numerical table called a color conversion table (LUT).

FIG. 9 is an explanatory diagram conceptually showing a color conversion table (LUT) referred to for color conversion processing. Now, it is assumed that gradation values of RGB colors can take values from 0 to 255. Further, as shown in FIG. 9, when considering a color space in which gradation values of R, G, and B are taken on three orthogonal axes, all RGB image data have a side length of 255 with the origin as a vertex. Can be associated with points inside the cube (color solid). From a different perspective, this can be thought of as follows. That is, when a color solid is subdivided into a grid perpendicular to each RGB axis and a plurality of grid points are generated in the color space, RGB image data corresponding to each grid point exists. Therefore, a combination of C, M, Y, and K gradation values is stored in advance at each lattice point. By doing this, it is possible to quickly convert the RGB image data into image data (CMYK image data) expressed by the tone values of each color by reading the tone values stored in the grid points. .

For example, if the R component of the image data is RA, the G component is GA, and the B component is BA,
This image data is associated with point A in the color space (see FIG. 9). Therefore, a cube dV containing point A is detected from small cubes that subdivide the color solid into a lattice shape, and the gradation values of the CMYK colors stored in the lattice points of the cube dV are read out. Then, if the interpolation calculation is performed from the gradation values of these grid points, the gradation value at the point A can be obtained. As described above, the color conversion table LUT is a three-dimensional number in which a combination of gradation values of CMYK colors (CMYK image data) is stored at each grid point indicated by a combination of gradation values of RGB colors. It can be considered as a table, and by referring to the color conversion table, RGB image data can be quickly converted into CMYK image data.

When the color conversion process is completed as described above, the control circuit 260 starts the halftone process as shown in FIG. 8 (step S154). Halftone processing is the following processing. The CMYK image data obtained by the color conversion process is image data expressed in the range of gradation value 0 to gradation value 255 for each color of C, M, Y, and K. In contrast, since the printer unit 200 prints an image by forming dots, the CMYK image data expressed by 256 gradations is converted into image data (dot data) expressed by the presence / absence of dot formation. Processing is required. Halftone processing is CM
This is processing for converting image data of each color YK into dot data.

As a method for performing the halftone process, various methods such as an error diffusion method and a dither method can be applied. The error diffusion method is to determine whether or not dots are formed for a certain pixel so as to diffuse an error in gradation expression generated in that pixel to surrounding pixels and to eliminate the error diffused from the surroundings. This is a method of determining the presence or absence of dot formation for each pixel. Also, the dither method uses a threshold value and CM that are randomly set in the dither matrix.
Comparing the image data of each color of YK for each pixel, it is determined that a dot is formed for a pixel having a larger image data, and conversely, a dot is not formed for a pixel having a larger threshold value. In this method, dot data for each pixel is obtained for each ink color.

FIG. 10 is an explanatory diagram illustrating an enlarged part of the dither matrix. In the illustrated matrix, threshold values that are uniformly selected from the range of gradation values 0 to 255 are randomly stored in a total of 4096 pixels, 64 pixels in the vertical and horizontal directions. Here, the threshold gradation value is 0.
In the present embodiment, the image data of each color of CMYK is 1-byte data and the gradation value can take a value of 0 to 255. still,
The size of the dither matrix is not limited to 64 pixels in the vertical and horizontal directions as illustrated in FIG. 10, but can be set to various sizes including those having different numbers of vertical and horizontal pixels. .

FIG. 11 is an explanatory diagram conceptually showing a state in which the presence / absence of dot formation is determined for each pixel with reference to the dither matrix. This determination is made for each color of CMYK, but in the following, in order to avoid complicated explanation, image data of each color of CMYK is simply referred to as image data without being distinguished.

When determining the presence or absence of dot formation, first, the gradation value of the image data for the pixel of interest (the pixel of interest) as the object of determination is compared with the threshold value stored at the corresponding position in the dither matrix. . The thin broken arrow shown in the figure schematically represents that the image data of the pixel of interest is compared with the threshold value stored at the corresponding position in the dither matrix. If the image data of the pixel of interest is larger than the threshold value of the dither matrix, it is determined that a dot is formed for that pixel. On the other hand, when the threshold value of the dither matrix is larger, it is determined that no dot is formed in the pixel.
In the example shown in FIG. 11, the image data of the pixel at the upper left corner of the image is “97”, and the threshold value stored at the position corresponding to this pixel on the dither matrix is “1”. Accordingly, for the pixel at the upper left corner, the image data is larger than the threshold value of the dither matrix, and therefore it is determined that a dot is formed on this pixel. An arrow indicated by a solid line in FIG. 11 schematically shows 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 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. Thus, by comparing the image data with the threshold value set in the dither matrix, it is possible to determine whether or not dots are formed for each pixel. In the halftone process (step S154 in FIG. 8), the above-described dither method is applied to the C, M, Y, and K image data to determine the presence or absence of dot formation for each pixel and to generate dot data. Generate the process.

Once the halftone process is performed as described above, the interlace process is started (step S156). The interlace process is a process in which the print head 241 rearranges the dot data in the order in which dots are formed and supplies them to the ink discharge heads 244 to 247 for each color. That is, as shown in FIG. 6, the ink discharge heads 244 to 247 are used.
Since the nozzles Nz provided in the nozzles are provided with an interval of the nozzle pitch k in the sub-scanning direction, when ink droplets are ejected while the print carriage 240 is main-scanned, the nozzle pitch k is spaced in the sub-scanning direction. As a result, dots are formed. Therefore, in order to form dots in all the pixels, the relative position between the print carriage 240 and the print medium is moved in the sub-scanning direction, and new dots are formed in the pixels between the dots separated by the nozzle pitch k. Necessary.
As described above, when an image is actually printed, dots are not formed in order from the upper pixel on the image. Furthermore, for pixels in the same row in the main scanning direction, instead of forming dots in a single main scan, the dots are divided into a plurality of main scans in response to image quality requirements. In this main scanning, dots are also widely formed on the pixels at the skipped positions.

For this reason, prior to actually starting dot formation, the dot data obtained for each color of C, M, Y, and K is rearranged in the order in which the ink ejection heads 244 to 247 form dots. Is required. Such a process is a process called interlace.

When the interlace process is completed, the control circuit 260 starts a process (dot formation process) for actually forming dots on the print medium in accordance with the dot data rearranged by the interlace process (step S158). That is, while the carriage motor 230 is driven to cause the print carriage 240 to perform main scanning, the rearranged dot data is supplied to the ink ejection heads 244 to 247. As described above, since the dot data is data indicating whether or not to form dots in each pixel, the ink ejection heads 244 to 2 are used.
If ink droplets are ejected according to dot data 47, ink dots can be appropriately formed in each pixel.

When one main scan is completed, the paper feed motor 235 is driven to feed the print medium in the sub-scanning direction, and the carriage motor 230 is driven again to print the print carriage 2.
The ink discharge head 244 converts the dot data rearranged in the order while 40 is main-scanned.
To 247 to form dots. By repeating these operations,
On the print medium, dots of each color of C, M, Y, and K are formed with an appropriate distribution according to the gradation value of the image data, and as a result, the image is printed.

As described above, in the image printing process, an image is printed by forming ink dots with an appropriate density on a print medium based on image data that has been corrected based on a feature amount in advance. Further, when correcting image data, correction is performed based on the feature quantity in the colorimetric color space, not the feature quantity obtained in the color space of the image data. For this reason, even if the color space in which the image data is described is different, all the image data can be handled uniformly according to the same standard, so that it is possible to correct appropriately. Hereinafter, a process (feature quantity extraction process) performed to extract a feature quantity in the colorimetric color space from the image data will be described in detail.

E. Feature amount extraction processing of the first embodiment:
FIG. 12 is a flowchart showing the flow of the feature amount extraction process of the first embodiment. In this embodiment, such processing is also executed by the control circuit 260 of the printing apparatus 10.

In the feature amount extraction process of the first embodiment, first, a process of reading color space information of image data is performed (step S200). Here, as described above, the color space conversion information is a standard color space (in this case, measurement data) obtained by setting color space data adopted by a device such as the digital camera 20 that generates image data as a standard. Color color space) data. The color space conversion information can be received in the form of a conversion formula or in the form of a so-called color profile. Further, the color space conversion information may be requested from the printing apparatus 10 side to a device that generates image data such as the digital camera 20 or may be received together with the image data from the digital camera 20 or the like. Also good.

Next, the data size of the received image data is compressed (step S202). In such processing, the pixels in the image are thinned out at a constant interval, thereby compressing the image data into a relatively small number of pixels such as 640 pixels × 480 pixels or 320 pixels × 240 pixels.

The compressed image data is converted into image data in the colorimetric color space according to the color space conversion information read in advance (step S204). As described above, the color space conversion information is information for converting color space data adopted by a device that generates image data into standard color space data set in advance as a standard. Is described in a format such as a conversion formula, a conversion matrix, or a so-called color profile. Of course, the color space conversion information only needs to be able to indirectly specify information described in these formats. For example, from among a plurality of conversion formulas stored in advance in the printing apparatus 10, It may be information specifying the corresponding item. In the feature amount extraction processing of this embodiment, since the data size of the image data is compressed in advance, the image data is converted into a standard color space (here, L * a * b * colorimetric color space) according to the color space conversion information. ) Can be quickly converted into image data.

By analyzing the image data thus converted into the colorimetric color space, the feature amount of the image is extracted (step S206). As the feature quantity to be extracted, various known feature quantities can be extracted. For example, a minimum gradation value, maximum gradation value, average value of gradation values, standard deviation, and a histogram of gradation values can be extracted from image data. Alternatively, as shown in FIG. 13, the image may be divided into a plurality of regions, and these feature amounts may be extracted for each region. When the feature quantity is obtained as described above, the feature quantity extraction process of the first embodiment shown in FIG. 12 is terminated, and after returning to the image printing process of FIG. 7, the processes after S104 are continued.

In the feature amount extraction process of the first embodiment described above, the received image data is converted into image data in the colorimetric color space in advance, and the feature amount is extracted by analyzing the image data in the colorimetric color space. The feature amount obtained in this way is the feature amount obtained in the colorimetric color space, regardless of the color space image data received from the image device such as the digital camera 20. For this reason, it is possible to handle the feature amount extracted from each image data in a unified manner without being affected by the difference in the color space used when generating the image data. It is possible to appropriately correct the image data and print a high-quality image. Further, if the image data is stored in the server together with the feature quantity obtained in this way, the feature quantity is data in the colorimetric color space even if the color space of the image data is different. Therefore, it is possible to search all image data in a unified manner, and it is possible to quickly find desired image data from a vast amount of image data.

F. Feature amount extraction processing of the second embodiment:
In the feature amount extraction process of the first embodiment described above, image data received from the digital camera 20 or the like is once converted into image data in a colorimetric color space, and the converted image data is analyzed to analyze the feature amount. Was extracted. However, it is also possible to extract the feature amount without converting the color space of the received image data, and to convert only the extracted feature amount into the colorimetric color space data. The feature amount extraction processing of the second embodiment described below is such processing.

FIG. 14 is a flowchart showing the flow of the feature amount extraction process of the second embodiment. The feature amount extraction processing of the second embodiment is greatly different from the processing of the first embodiment shown in FIG. 12 in that the feature amount is extracted and then the color space is converted. In the following, the feature amount extraction processing of the second embodiment will be described focusing on such differences.

When the feature amount extraction process of the second embodiment is started, the color space information of the image data is first read (step S300) and then the data of the read image data, as in the case of the first embodiment described above. A process of compressing the size is performed (step S302).

In the feature amount extraction process of the second embodiment, when the image data is compressed in this way, the image data is immediately analyzed to extract the feature amount (step S304). Although the image data to be analyzed is compressed in data size, the color space is the color space as received from the digital camera 20 or the like, so that the extracted feature amount can also be obtained as data in the color space of the image data. become. Therefore, the feature quantity obtained in this way cannot be handled uniformly for image data generated in different color spaces.

Therefore, in the feature amount extraction process of the second embodiment, when the feature amount is extracted, the feature amount is converted into a feature amount in the colorimetric color space (step S306). Since the color space conversion information for converting the color space data in which the image data is generated into the colorimetric color space data is read in advance in step S300, the extracted feature amount is determined according to the color space conversion information. It can be converted into a feature value of the colorimetric color space. When the feature quantity of the colorimetric color space is obtained in this way, the feature quantity extraction process of the second embodiment shown in FIG. 14 is finished, and after returning to the image printing process of FIG. 7, the processes after S104 are continued. .

In the feature amount extraction process of the second embodiment described above, the feature amount of the colorimetric color space can be obtained in the same manner as in the first embodiment described above, so what is the image data received from the image device such as the digital camera 20? Even in the case of image data in a simple color space, it is possible to handle the feature values uniformly without being affected by the difference in the color space.

In the feature amount extraction process of the first embodiment described above, image data is temporarily converted into a colorimetric color space and then feature amounts are extracted, whereas in the second embodiment, image data is extracted. Without conversion to the colorimetric color space, the feature amount is extracted as it is, and only the obtained feature amount is converted into the colorimetric color space data. For this reason, the process of converting the image data into the colorimetric color space is unnecessary, and the process can be speeded up.

On the other hand, in the feature amount extraction process of the first embodiment described above, since the entire image data is analyzed after being converted into the colorimetric color space, detailed analysis is possible, and the feature amount is extracted by that much. There is an advantage that it is possible to do.

G. Variations:
In the various embodiments described above, the image data analysis apparatus is incorporated in the printing apparatus 10, and when image data is received from an image device such as the digital camera 20, the image data is extracted after extracting the feature value of the colorimetric color space. Described as printed. However, the image data analysis device
For example, it is possible to generate image data as meta image data to which a feature amount is added by being incorporated in a device such as the digital camera 20 or the scanner 40 that generates image data. Below, such a modification is demonstrated.

FIG. 15 is a flowchart showing a flow of meta image generation processing performed to generate meta image data. Such processing is performed in an image device that generates image data, such as the digital camera 20, the computer 30, and the scanner 40. Hereinafter, processing for generating meta image data will be described with reference to a flowchart.

When the meta image data generation process is started, first, image data is generated (step S).
400). If the meta image data generation process is performed in the digital camera 20, for example, image data is generated by capturing an image. Alternatively, if the meta image data generation processing is performed in an application program running on the computer 30, image data is generated by the application program. Furthermore, when the meta image data generation process is performed when the scanner 40 reads an original image, the image data is generated by reading the original image.

Next, a process for compressing the data size of the generated image data is performed (step S402).
). In other words, by compressing pixels from the generated image data at regular intervals, the image data is compressed into image data having a relatively small number of pixels.

Thereafter, the compressed image data is converted into image data in a colorimetric color space (step S40).
4). At the time of conversion, color space conversion information stored in advance is read, and image data is converted according to the conversion information. As described above, the color space conversion information is information for converting the color space data generated from the image data into the standard color space data set in advance as a standard. Furthermore, it is described in a format such as a so-called color profile.

Next, by analyzing the image data converted into the colorimetric color space, the feature amount of the image is extracted (step S406). Thereafter, when meta image data is generated by attaching the extracted feature amount to the header portion of the previously generated image data (step S408), FIG.
The meta image data generation process shown in FIG. FIG. 16 is an explanatory diagram conceptually showing a state in which a feature amount is added to the header portion of the image data.

In the meta image data generated as described above, the feature amount in the colorimetric color space is attached to the header portion. For this reason, it is possible to handle the feature values uniformly regardless of the color space, regardless of the color space. As a result, for example, when an image is printed (or displayed on the screen), it is possible to appropriately correct the image data according to the feature amount to obtain a high-quality image. Also, by storing such meta-image data in the server, it becomes possible to search all image data uniformly from a huge amount of image data based on the feature amount, and the desired image data Can be found quickly.

Although the printing apparatus of the present embodiment has been described above, the present invention is not limited to all the above-described embodiments, and can be implemented in various modes without departing from the scope of the present invention.

It is explanatory drawing which showed the outline | summary of the image data analysis apparatus of a present Example. 1 is a perspective view showing an external shape of a printing apparatus in which an image data analysis apparatus according to an embodiment is incorporated. FIG. 3 is an explanatory diagram showing a state in which a document table cover provided on the upper part of the printing apparatus is opened to read a document image. It is the perspective view which showed a mode that the front side of the scanner part was lifted and rotated. It is explanatory drawing which showed notionally the internal structure of the printing apparatus of a present Example. It is explanatory drawing which showed a mode that the several nozzle which discharges an ink drop to the ink discharge head of each color was formed. 3 is a flowchart illustrating a flow of image printing processing performed to print an image with the printing apparatus according to the present exemplary embodiment. 6 is a flowchart illustrating a flow of image forming processing for forming an image using ink dots on a print medium. It is explanatory drawing which showed notionally the color conversion table referred for a color conversion process. It is explanatory drawing which expanded and illustrated a part of dither matrix. It is explanatory drawing which showed notionally the mode that the presence or absence of dot formation was judged for every pixel, referring a dither matrix. It is a flowchart which shows the flow of the feature-value extraction process of 1st Example. It is explanatory drawing which showed a mode that the image was divided | segmented into several area | region in order to extract the feature-value. It is a flowchart which shows the flow of the feature-value extraction process of 2nd Example. It is a flowchart which shows the flow of the meta image production | generation process performed in order to produce | generate meta image data. It is explanatory drawing which showed notably the mode that the feature-value is added to the header part of image data.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Printing apparatus, 12 ... Ink discharge head, 100 ... Scanner part, 200 ... Printer part, 240 ... Print carriage, 241 ... Print head, 242 ... Ink cartridge, 243
... ink cartridge, 260 ... control circuit, 300 ... operation panel.

Claims (13)

An image data analysis apparatus that extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
Image data receiving means for receiving image data of an image from which the feature amount is to be extracted;
Color space conversion information acquisition means for acquiring color space conversion information for converting the received image data into image data of a standard color space which is a color space set as a standard in advance;
Image data conversion means for converting the received image data into image data of the standard color space based on the color space conversion information;
An image data analysis apparatus comprising: feature amount extraction means for extracting the predetermined feature amount by analyzing the image data converted into the standard color space. An image data analysis apparatus that extracts a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
Image data receiving means for receiving image data of an image from which the feature amount is to be extracted;
Color space conversion information acquisition means for acquiring color space conversion information for converting data of a color space in which the image data is described into data of a standard color space that is a color space set in advance as a standard;
Analyzing the received image data to extract the predetermined feature amount; and
An image data analysis apparatus comprising: a feature amount conversion unit that converts the extracted feature amount into a feature amount in the standard color space by converting the extracted feature amount based on the color space conversion information. The image data analysis device according to claim 1 or 2, wherein
The color space conversion information acquisition unit is an image data analysis device that acquires, as the color space conversion information, information for converting color space data in which the image data is described into colorimetric color space data. A meta image data generating device that generates meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing an image,
Image data receiving means for receiving the image data;
Color space conversion information acquisition means for acquiring color space conversion information for converting the received image data into image data of a standard color space which is a color space set as a standard in advance;
Image data conversion means for converting the received image data into image data of the standard color space based on the color space conversion information;
Analyzing the image data converted into the standard color space to extract the predetermined feature amount; and
A meta image data generation device comprising: metadata adding means for generating the meta image data by adding the extracted feature amount as the metadata to the received image data. A meta image data generating device that generates meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing an image,
Image data receiving means for receiving the image data;
Color space conversion information acquisition means for acquiring color space conversion information for converting data of a color space in which the image data is described into data of a standard color space that is a color space set in advance as a standard;
Analyzing the received image data to extract the predetermined feature amount; and
A feature amount conversion means for converting the extracted feature amount into a feature amount in the standard color space by converting the extracted feature amount based on the color space conversion information;
A meta image data generating device comprising: metadata adding means for generating the meta image data by adding the converted feature quantity as the metadata to the received image data. An image data analysis method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
A first step of receiving image data of an image from which the feature amount is to be extracted;
A second step of acquiring color space conversion information for converting the received image data into image data of a standard color space which is a color space set in advance as a standard;
A third step of converting the received image data into image data of the standard color space based on the color space conversion information;
And a fourth step of extracting the predetermined feature amount by analyzing the image data converted into the standard color space. An image data analysis method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
Receiving (A) image data of an image from which the feature amount is to be extracted;
(B) obtaining color space conversion information for converting color space data in which the image data is described into data of a standard color space that is a color space set in advance as a standard;
A step of extracting the predetermined feature amount by analyzing the received image data (
C) and
A process (D) for converting the extracted feature quantity into a feature quantity in the standard color space by converting the extracted feature quantity based on the color space conversion information. A meta image data generation method for generating meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing an image,
Receiving the image data (1);
Obtaining (2) color space conversion information for converting the received image data into image data of a standard color space which is a color space set in advance as a standard;
(3) converting the received image data into image data of the standard color space based on the color space conversion information;
Analyzing the image data converted into the standard color space to extract the predetermined feature amount (4);
A meta image data generation method comprising: (5) generating the meta image data by adding the extracted feature amount as the metadata to the received image data. A meta image data generation method for generating meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing an image,
Receiving the image data (A);
Obtaining (b) color space conversion information for converting the data of the color space in which the image data is described into data of a standard color space that is a color space set in advance as a standard;
A step of extracting the predetermined feature amount by analyzing the received image data (
C)
Converting the extracted feature quantity based on the color space conversion information into a feature quantity in the standard color space (D);
A meta image data generation method comprising: (e) generating the meta image data by adding the converted feature amount as the meta data to the received image data. A program for realizing, using a computer, a method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
A first function for receiving image data of an image from which the feature amount is to be extracted;
A second function of acquiring color space conversion information for converting the received image data into image data of a standard color space which is a color space set in advance as a standard;
A third function for converting the received image data into image data of the standard color space based on the color space conversion information;
A program that uses a computer to realize the fourth function of extracting the predetermined feature amount by analyzing the image data converted into the standard color space. A program for realizing, using a computer, a method for extracting a predetermined feature amount from an image represented by the image data by performing predetermined image analysis on the image data,
A function (A) for receiving image data of an image from which the feature amount is to be extracted;
A function (B) for obtaining color space conversion information for converting data of a color space in which the image data is described into data of a standard color space which is a color space set in advance as a standard;
A function of extracting the predetermined feature amount by analyzing the received image data (
C) and
The program which implement | achieves the function (D) converted into the feature-value in the said standard color space using a computer by converting the extracted feature-value based on the said color space conversion information. A program for realizing, using a computer, a method of generating meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing the image. ,
A function (1) for receiving the image data;
A function (2) for obtaining color space conversion information for converting the received image data into image data of a standard color space which is a color space set in advance as a standard;
A function (3) for converting the received image data into image data of the standard color space based on the color space conversion information;
A function (4) for extracting the predetermined feature amount by analyzing the image data converted into the standard color space;
A program for realizing the function (5) for generating the meta image data by adding the extracted feature amount as the metadata to the received image data using a computer. A program for realizing, using a computer, a method of generating meta image data as image data accompanied by metadata by adding metadata indicating information about the image to image data representing the image. ,
A function (a) for receiving the image data;
A function (a) for obtaining color space conversion information for converting data of a color space in which the image data is described into data of a standard color space that is a color space set in advance as a standard;
A function of extracting the predetermined feature amount by analyzing the received image data (
C)
A function (d) for converting the extracted feature quantity based on the color space conversion information into a feature quantity in the standard color space;
A program for realizing the function (e) for generating the meta image data by adding the converted feature quantity as the metadata to the received image data using a computer.

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