JPH08307690A - Image processing unit - Google Patents

Abstract

PURPOSE: To generate an image excellent in gradation and resolution. CONSTITUTION: A multi-value original image is divided into plural image blocks and a 2-path edge detection section 321 detects an edge from each image block and the image block is classified into plural patterns depending on the presence of an edge component of an obtained two longitudinal and lateral areas. Then a binarization pattern decision section 322 forms a dither block and an original image is binarized by the dither block.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing device for developing a multi-valued image into a binarized image.

[0002]

2. Description of the Related Art In a conventional color ink jet printer, for example, input data composed of multi-valued RGB data is converted from RGB values to YMCK values by color conversion processing inside the printer via an interface. Furthermore, an image is generated by the expansion processing provided inside, and Y
After obtaining MCK multi-valued data, binarization processing is performed to obtain final drawing data.

In order to reproduce a gradation image in a binary display device in which the density that can be expressed by one dot cannot be changed like the color ink jet printer having the above structure, local noise is added to the original image. Therefore, a so-called dither method, which reproduces the gradation in a pseudo manner, is widely known. Since the dither method utilizes the fact that human beings have a low spatial frequency characteristic, that is, the perception of high frequency components is low, it is desirable that the noise has a sufficiently high frequency so that it cannot be perceived.

[0004]

However, in the binarization method based on the dither method, there is a problem in principle that the improvement in gradation and the improvement in resolution are in a trade-off relationship. For example, considering the reproduction of smooth halftone image signals,
In order to reproduce this halftone, it is necessary to realize as high gradation as possible. Then, in order to obtain high gradation, it is necessary to make the unit area to which the dither is added large, but this inevitably results in a decrease in resolution.

The present invention has been made in view of the above problems, and an object thereof is to provide an image processing apparatus which can easily generate an image excellent in gradation and resolution.

[0006]

In order to achieve the above object, the present invention is an image processing apparatus for developing a multi-valued image into a binary image to generate an image, in which the multi-valued image is divided into a plurality of image blocks. Means for dividing the image block into two parts, and edge detection means for detecting edges of a plurality of paths for each image block,
Means for classifying the image block into a plurality of predetermined patterns based on the edge detection result, means for forming a dither block by the plurality of classified patterns, and binarization processing based on the dither block And means for applying.

[0007]

With the above construction, it functions to generate an image excellent in gradation and resolution.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. [First Embodiment] First, a first embodiment of the present invention will be described. <Description of Color Printer Device> FIG. 1 is a view showing the schematic arrangement of a color printer device according to this embodiment. In the figure, reference numerals 220 to 223 are color ink cartridges. The cartridge 220 has yellow (Y) color ink, the cartridge 221 has magenta (M) color ink, and the cartridge 222 has cyan (C) color ink. The cartridge 223 is filled with black (K) color ink.

Independent pipes extend from the color ink cartridges and are connected to the pressure pump 216. Each ink is sent from the pressure pump 216 to the print head 212 at a constant pressure.

The printing paper is the color printer device 201.
The paper is fed from the rear surface and is fixed by a paper platen 211 and a front guide roller 215. The color printer device is operated by pressing a key button on the control panel 218, and the controller board 219 controls all operations of the color printer device 201.

In order to perform printing on the color printer device 201, a print control command and print data are sent via an interface (not shown). For example, when the RGB color is designated by the color designation command, the control board 219 controls the RGB color to YMC via the internal color processing device.
After conversion into K data, the print head 212 is driven to print. <Description of Processing Outline> FIG. 2 is a block diagram showing the internal processing of the color printer apparatus according to this embodiment. As shown in the figure, the input data 310 composed of multi-valued RGB data is converted from the RGB value to the Y value by the color conversion processing unit 312 inside the printer apparatus via the interface 311.
Converted to MCK value. Further, by generating an image in the expansion processing unit 313, the YMCK multivalued data 314 is generated.
Get.

With respect to the multi-valued data 314, the 2-pass edge detection section 321 executes edge detection of 2 passes for each region, and the binarization pattern in each region is binarized based on the result. The pattern determining unit 322 determines the pattern. Also,
The binarization unit 315 binarizes the multivalued data 314 by the binarization pattern determined by the 2-pass edge detection unit 312, and finally obtains the drawing data 316. <Cutout of Block> FIG. 3 shows a rectangular region (hereinafter referred to as image block 42) from the image 411 in this embodiment.
FIG. 3 is a diagram schematically showing a state in which (1) is cut out and analyzed.

The image block size to be cut out here is Xn in the horizontal direction and Yn in the vertical direction. For example, when a block is cut out from a certain image and the pixel densities in the block are plotted on a graph, the distribution shown in the graph 431 is obtained. <Detection of Image Edge Component by 2-Pass> X in FIG.
0 and Y0 are values obtained by extracting the edge components of the vertical and horizontal two regions of the image block 421, and these are obtained as follows. That is, how to obtain path 1: the edge component in the X direction in the block area is obtained by the following equation (1), and this is set as Ex0. Then, the value of Ex0 and the threshold function Tx0 ()
To determine the value of X0.

(Equation 1) However, the function wx () is a function that defines weighting,
The function f () is a function that represents the input image signal in the block, and the function gx () is a function that defines the horizontal edge signal. Then, for X0, the values are as follows: X0 = 0 (when Ex0 ≦ Tx0 ()) X0 = 1 (when Ex0> Tx0 ()). However, the function Tx0 () is a function that provides a random output value whose average value is approximately Mx0. Here, Mx0 is a constant appropriately determined (experimentally or quantitatively) according to the characteristics of the image or the system.

How to obtain path 2: The edge component in the Y direction in the block area is obtained by the following equation (2), and this is Ey0. Then, the value of Ey0 is compared with the threshold value function Ty0 () to determine the value of Y0.

(Equation 2) However, the function wy () is a function that defines weighting,
The function f () is a function that represents an input image signal in the block, and the function gy () is a function that defines a vertical edge signal. Regarding Y0, Y0 = 0 (when Ey0 ≦ Ty0 ()) and Y0 = 1 (when Ey0> Ty0 ()). However, the function Ty0 () has an average value of approximately M.
A function that provides a random output value as y0, and M
y0 depends on the characteristics of the image or system (experimentally,
Or (quantitatively) an appropriately determined constant. <Classification of Paint Patterns by Edge Component Values> FIG. 4 is a map showing the above-mentioned classification of paint patterns by edge component values. As shown in the figure, here, the paint patterns in the block are classified according to four kinds of possible values of X0 and Y0 (0 indicates no edge, 1 indicates edge).

For the sake of convenience, the coating pattern is defined as a square type, a square type is an I type, and a combination thereof. However, with respect to these patterns, rotated patterns are not distinguished, but their sizes are distinguished. Specifically, as shown in FIG. 4, when the edge component of the region X0, Y0 is 0, 0, there is one square type (large), and when the edge component of the region X0, Y0 is 0, 1, I There are two types. When the edge component of the region X0, Y0 is 1,0, there are two I types. When the edge component of the region X0, Y0 is 1,1, the square type (small) is classified as four. <Description of Binarization Method> FIG. 5 is a conceptual diagram showing a manner of assembling a painting pattern based on the above-mentioned painting pattern classification and binarizing a multi-valued original image. In the figure, after the original image 611 is divided into image blocks, a 2-pass edge component detection is performed in block B621, and a painting pattern is generated in block B622 according to the processing result.

In this block B622, the dither block (square type, I type) is classified according to the classification shown in FIG.
Type), for example, by looking up a lookup table or the like,
Appropriate combinations are used to generate a painting pattern. Then, the image is binarized by applying this generation pattern.

As described above, according to this embodiment,
The multi-valued original image is divided into a plurality of image blocks, and the dither blocks are formed by classifying the image blocks into a plurality of patterns according to the presence or absence of edge components of two vertical and horizontal regions detected for each of these image blocks. By binarizing the original image, it is possible to reproduce the edge component buried in the image block, and at the same time, the gradation reproducibility can be improved by widening the dither area other than the edge portion. [Second Embodiment] A second embodiment according to the present invention will be described below. <Explanation of Processing Outline> FIG. 6 is a block diagram showing the internal processing of the color inkjet printer according to the present embodiment. As shown in the figure, input data 710 composed of multi-valued RGB data is converted from RGB values to YMCK values by a color conversion processing unit 712 inside the printer via an interface 711. The converted signal is
An image is generated in the expansion processing unit 713, and YMCK multivalued data 714 is obtained.

With respect to this multi-valued data 714, the 3-pass edge detection unit 721 performs 3-pass edge detection for each region, and based on this result, the binarized pattern in each region is determined. The determination is made in part 722. Then, in the binarization unit 715, the binarization pattern determination unit 722.
The multi-valued data 714 is binarized according to the binarization pattern determined in step S4, and finally the drawing data 716 is obtained. <Cutout of Block> FIG. 7 shows how a rectangular area (hereinafter referred to as an image block 821) is cut out from an image (multi-valued image) 811 in the present embodiment.
Here, the image block size to be cut out is Xn in the horizontal direction and Yn in the vertical direction. For example, when a block is cut out from an image and the pixel densities in this block are plotted on a graph, a distribution like the graph 831 in FIG. 7 is shown. <Image Edge Component Detection by 3-Pass> X in FIG.
0, X1, and Y0 are values obtained by extracting the edge components of the three areas of the image block 821, and they are obtained as follows.

How to obtain path 1: area (Yi = 0 to Yn /
2; Xi = 0 to Xn), the edge component in the X direction is obtained by the following equation (3), and this is set to Ex0.
Then, the value of Ex0 is compared with the threshold value function Tx0 () to determine the value of X0.

(Equation 3) However, the function wx () is a function that defines weighting, the function f () is a function that represents an input image signal in a block, and the function gx () is a function that defines a horizontal edge signal. Regarding X0, X0 = 0 (when Ex0 ≦ Tx0 ()) X0 = 1 (when Ex0> Tx0 ()). However, the function Tx0 () is a function that provides a random output value whose average value is approximately Mx0.
x0 depends on the characteristics of the image or system (experimentally,
Or (quantitatively) an appropriately determined constant.

How to obtain path 2: area (Yi = Yn / 2 to 2)
Yn; Xi = 0 to Xn), the edge component in the X direction is obtained by the following equation (4), and this is defined as Ex1.
Then, the value of Ex1 is compared with the threshold value function Tx1 () to determine the value of X1.

(Equation 4) However, the function wx () is a function that defines weighting,
The function f () is a function that represents an input image signal in the block, and the function gx () is a function that defines a horizontal edge signal. Regarding X1, X1 = 0 (when Ex1 ≦ Tx1 ()) X1 = 1 (when Ex1> Tx1 ()). However, the function Tx1 () is a function that provides a random output value whose average value is approximately Mx1.
x1 depends on the characteristics of the image or system (experimentally,
Or (quantitatively) an appropriately determined constant.

How to obtain path 3: area (Xi = 0 to Xn /
2; Yi = 0 to Yn), the edge component in the Y direction is obtained by the following equation (5), and this is Ey0.
Then, the value of Ey0 is compared with the threshold value function Ty0 () to determine the value of Y0.

[Formula 5] However, the function wy () is a function that defines weighting,
The function f () is a function that represents an input image signal in the block, and the function gy () is a function that defines a vertical edge signal. Regarding Y0, Y0 = 0 (when Ey0 ≦ Ty0 ()) and Y0 = 1 (when Ey0> Ty0 ()). However, the function Ty0 () is a function that provides a random output value whose average value is approximately My0.
y0 depends on the characteristics of the image or system (experimentally,
Or (quantitatively) an appropriately determined constant. <Classification of Paint Patterns by Edge Component Values> FIG. 8 is a map showing classification of paint patterns by edge component values in this embodiment. Here, possible values of X0, X1, Y0 (0 indicates no edge, 1 indicates edge)
The paint patterns in the block are classified according to the eight types.

Here, for the sake of convenience, the coating pattern is defined as a square type, a square type is an I type, and a square type is an L type, and is formed by a combination thereof. However, although these patterns do not distinguish rotated or inverted patterns, their sizes are distinguished. Specifically, FIG.
As shown in, when the edge component of the region X0, X1, Y0 is 0, 0, 0, there is one square type (large) I when the edge component of the region X0, X1, Y0 is 0, 0, 1 Two types of regions When the edge components of the regions X0, X1, Y0 are 0, 1, 0, L type + square type (small) When the edge components of the regions X0, X1, Y0 are 0, 1, 1, When the edge component of L type + square type (small) region X0, X1, Y0 is 1, 0, 0, the edge component of L type + square type (small) region X0, X1, Y0 is 1, 0, 1 When, the L-type + square type (small) area X0, X1, Y0 has edge components of 1, 1, 0, and two I-type areas X0, X1, Y0 have edge components of 1, 1, 1 In case of, the square type (small) is classified into four. <Description of Binarization Method> FIG. 9 is a conceptual diagram showing how a multi-value original image is binarized by assembling a paint pattern based on the above-mentioned paint pattern classification. In the figure, after dividing the original image 1011 into image blocks,
In block B1021, 3-pass edge component detection is performed, and a painting pattern is generated in block B1022 based on the processing result.

In block B1022, the dither block (square type, I type) is classified according to the classification shown in FIG.
Type, L type) are appropriately combined by referring to, for example, a lookup table or the like to generate a paint pattern, and the generated pattern is applied to binarize the image.

As described above, according to this embodiment,
The multi-valued original image is divided into a plurality of image blocks, and the dither blocks are formed by classifying the image blocks into a plurality of patterns according to the presence or absence of edge components in the vertical and horizontal three regions detected for each of these image blocks. By binarizing the original image, it is possible to reproduce the edge component buried in the image block, and at the same time, the gradation reproducibility can be improved by widening the dither area other than the edge portion.

The present invention may be applied to a system including a plurality of devices or an apparatus including a single device. Further, it goes without saying that the present invention can be applied to the case where it is achieved by supplying a program to a system or an apparatus.

[0026]

As described above, according to the present invention,
Edge detection and gradation reproducibility can be improved by detecting the edges of multiple passes for locally separated images and determining the paint pattern based on the results, and the gradation and resolution can be improved throughout the image. Excellent images can be easily generated.

[0027]

[Brief description of drawings]

FIG. 1 is a diagram showing a schematic configuration of a color printer device according to a first embodiment of the invention.

FIG. 2 is a block diagram showing an internal process of the color printer apparatus according to the first embodiment.

FIG. 3 is a diagram schematically showing how a rectangular region is cut out and analyzed in the first embodiment.

FIG. 4 is a diagram showing a painting pattern classification according to edge component values.

FIG. 5 is a conceptual diagram showing how a multivalued original image is binarized based on a painting pattern classification.

FIG. 6 is a block diagram showing internal processing of a color inkjet printer according to a second embodiment.

FIG. 7 is a diagram showing how a rectangular area is cut out in the second embodiment.

FIG. 8 is a diagram showing classification of painting patterns according to edge component values in the second embodiment.

FIG. 9 is a conceptual diagram showing how a multivalued original image is binarized based on a painting pattern classification.

[Explanation of symbols]

 201 Color printer device 211 Paper platen 212 Print head 216 Pressure pump 215 Front guide roller 218 Control panel 219 Controller board 220 to 223 Color ink cartridge 310,710 Input data 311,711 Interface 312,712 Color conversion processing unit 313,713 Development processing Part 314, 714 Multi-valued data 315, 715 Binarization part 316, 716 Drawing data 321 Two-path edge detection part 322, 722 Binarization pattern determination part 721 Three-path edge detection part

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Internal reference number FI Technical display location G06T 5/00 G06F 15/68 320A

Claims (4)

[Claims] 1. An image processing device for expanding a multi-valued image into a binary image to generate an image, means for dividing the multi-valued image into a plurality of image blocks, and an edge of a plurality of paths for each of the image blocks. Edge detecting means for performing detection, means for classifying the image block into a plurality of predetermined patterns based on the edge detection result, means for forming a dither block by the plurality of classified patterns, An image processing apparatus comprising: a unit that performs a binarization process based on a dither block. 2. The edge detecting means further determines a presence / absence of a sharp density change in the horizontal direction of the image block, and a presence / absence of a sharp density change in the vertical direction of the image block. The image processing apparatus according to claim 1, further comprising: 3. The image processing apparatus according to claim 1, wherein the plurality of paths are vertical and horizontal bidirectional paths for the image block. 4. The image processing apparatus according to claim 1, wherein the plurality of passes are passes in the vertical and horizontal directions of the image block.