JPH07334648A - Method and device for processing image - Google Patents

Abstract

PURPOSE:To reduce the quantity of image data and also to variably magnify the images with high picture quality by extracting the color and the shape of a monochromatic area of an inputted color image and then extracting the vector coordinates to show the boundary of the monochromatic area based on its shape. CONSTITUTION:A monochromatic area extracting part 102 extracts the monochromatic areas out of the color images of raster scan forms which are received from a color image acquiring part not and outputs the information on the positions, colors, etc., of the extracted monochromatic areas and the binary partial images corresponding to these monochromatic areas. A plural-outline extracting part 103 extracts a rough contour vector out of the binary partial image of each monochromatic area. A plural- outline smoothing/variable power part 104 smoothes the rough contour vector data on each monochromatic area in a vector data form and applies the variable power processing to the smoothed vector data. A color image reproducing part 105 reproduces the color image data of raster scan system having an area of a shape that is shown by the contour vector data and displays the image data at an output part 106 based on the contour vector data received from the part 104 and the color of the monochromatic area.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus for performing smoothing, scaling, etc. on the basis of vector coordinates representing a monochrome area in a color image.

[0002]

2. Description of the Related Art In recent years, input / output devices capable of inputting / outputting color images have become widespread in the OA field. With this,
The number of processes that handle color text images (color images that occupy most of black-and-white portions and limited-color portions) is also increasing. As a method of scaling a color image, the pixels of the original image are periodically thinned (when reducing) according to the scaling factor, or repeatedly output (when enlarging) according to the scaling factor. And a method of performing coordinate conversion (affine conversion, etc.) on each component (RGB, etc.) of the color image and then interpolating neighboring values to obtain scaled image data.

As a method of reducing the amount of image data when storing or communicating color images, JPEG (Joint Photograp)
Discrete cosine transform (DC by hic Expert Group)
There is a data compression method such as an encoding method using T).
In addition, after converting a color image to a uniform color space, the region is divided using the color difference, the shape of the region is chain-coded, and the hue is roughly quantized using the memory color for each region, and the saturation is calculated. Is a polynomial approximation for each region, and a method for encoding a color image by further encoding the brightness with adaptive discrete cosine transform coding (IEICE Transactions BI Vol.75-B
-I No.6 pp422-430 June 1992) is proposed.

On the other hand, as a method of extracting a monochrome region from a color image, a recursive threshold method (structuring of color image information by region division processing, information processing, Vol. 19, No. 12, Dec, 197) is used.
8, pp.1130-11369). This method recursively repeats, for each of the cut-out regions, a process of cutting out regions by determining a threshold value for region division from the valleys of the histogram in the color component features of RGB, HSI, and YIQ for a color image. Method or limited color expression method (a color quantization method that repeatedly divides the color distribution until the number of colors that human eyes cannot identify the color error reaches) is used (1990 Spring National Convention of the Institute of Electronics, Information and Communication Engineers) D4167
-168).

Japanese Patent Application No. 3-34506, which has been filed by the applicant, is a method for expressing an image area in vector coordinates and performing smoothing / magnification based on the vector coordinates. The device disclosed therein relates to a device for extracting contour line information of a binary image, smoothing and scaling, extracting an outline vector from the binary image, and selecting a desired scaling factor in the state of the extracted outline vector expression. Create a smoothly scaled outline vector at (arbitrary) and regenerate a binary image from this smoothly scaled outline vector to obtain a high-quality digital image at a desired magnification (arbitrary). A binary image is obtained.

[0006]

However, the above-described scaling method using thinning and repetition has a problem in image quality because the shaded portions are stepwise. Further, the scaling method using coordinate conversion is effective for continuous tone portions of a color image, but has a disadvantage that edges are blurred due to interpolation processing in a character / line image portion such as a character or a graph. there were.

Further, the above-described method of storing color images and reducing the amount of data at the time of communication is also effective for continuous tone portions of color images, but the image quality is deteriorated in the character and line drawing portions such as characters and graphs. There was a big problem. In addition, since the method of performing region division and encoding is also applied to continuous tone color images, the lightness is adaptive discrete cosine transform coded, and the lightness information occupies most of the total information amount. Therefore, such an encoding method is effective for a continuous tone portion of a color image, but most of the black and white portion and limited color portion, and for a document image in which the lightness information is less important, The coding efficiency will be poor.

On the other hand, each of the above-described methods for extracting a monochrome region from a color image is considered for the extraction of a monochrome region, but is also considered for application to subsequent processing such as smoothing / magnification, storage, and communication. Not not. In addition, Japanese Patent Application No. 3-34 for performing smoothing and scaling using the vector coordinate representation of the area
506 is effective for extraction of contour line information of a binary image and smoothing / scaling, but is directly applied to extraction of contour line information of a monochrome area input as a color image and smoothing / scaling processing. I couldn't.

The present invention has been made in view of the above conventional example, and extracts a monochromatic region in a color image, obtains contour line information of the extracted monochromatic region, and obtains a high-quality color image based on the contour line information. It is an object of the present invention to provide an image processing method and apparatus capable of performing smoothing and scaling of the image.

It is another object of the present invention to provide an image processing method and apparatus capable of scaling image data while reducing the amount of image data and maintaining high image quality.

[0011]

In order to achieve the above object, the image processing apparatus of the present invention has the following configuration.
That is, an image input unit for inputting a color image, a monochrome region extracting unit for extracting the color and shape of a monochrome region in the color image input from the image input unit, and a monochrome region extracted by the monochrome region extracting unit. Vector extraction means for extracting vector coordinates representing the boundary of the monochrome region based on the shape.

In order to achieve the above object, the image processing method of the present invention comprises the following steps. That is, an image processing method for expressing a monochrome area of a color image by a color of the area and vector coordinates representing a boundary of the area, and a monochrome area extracting step of extracting a color and a shape of the monochrome area from the color image, and Extracting vector coordinates representing the boundary line of the single color area from the shape of the extracted single color area.

[0013]

With the above arrangement, a color image is input, and the color and shape of the monochrome region in the input color image are extracted. Based on the shape of the extracted monochromatic area,
It operates to extract the vector coordinates that represent the boundaries of the monochromatic area.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT A preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings. In the present embodiment, the monochrome region is an arbitrary pixel formed of pixels having a single value such as black and white or limited color (pixels having a value within a certain color difference, not necessarily having the same value). It refers to the image area of the shape, and the pixels in the area do not necessarily need to be connected. The method and apparatus according to the present embodiment can be used for a device that handles color text images. For example, at the time of edit processing (enlargement / reduction) in a DTP (Desk Top Publishing) apparatus, a color printer
It can also be used for smoothing / magnifying processing (pixel density conversion) when outputting a color image in an image output device such as a color facsimile. It can also be used for reducing the amount of data when performing color image communication in a communication device such as a color facsimile machine or a network such as a LAN, or when storing a color image in a storage device such as a magnetic disk.

[First Embodiment] FIG. 1 is a functional block diagram showing the functional arrangement of an embodiment of the present invention.

In FIG. 1, a color image acquisition unit 101
Acquires (inputs) a digital color image to be processed,
Outputs a raster scan format color image. The monochromatic area extracting unit 102 extracts monochromatic areas from the raster scanning format color image output from the color image acquisition unit 101, and outputs information such as a binary partial image corresponding to each monochromatic area and the position and color of the area. To do. The multiple outline extraction unit 103 extracts a rough contour vector from the binary partial image of each monochrome region. The multiple outline smoothing / scaling unit 104 smoothes and scales the rough contour vector data of each monochromatic area in a vector data format. The color image reproducing unit 105 reproduces the color image data of the raster scanning format having the area of the shape represented by the contour vector data from the contour vector data output from the outline smoothing / magnifying unit 104 and the color of the monochrome area. The color image output unit 106
It has a function of displaying color image data in a raster scan format, making a hard copy, or outputting to a communication path.

A detailed description will be given below.

<Color Image Acquisition Unit 101> The color image acquisition unit 101 is composed of, for example, a known raster scanning type image output device which reads an image by a color image reader and outputs it in a raster scanning format. As this image output device, a known raster scan type image output device that receives a color image from a communication path and outputs it in a raster scan format, or
A known raster scanning type image output device that reads a color image from an image storage device such as an image file and outputs the color image in a raster scanning format may be used.

<Monochromatic Region Extraction Unit 102> Next, the monochromatic region extraction unit 102 inputs the raster scanning format color image output from the color image acquisition unit 101 to extract monochromatic regions, and corresponds to each monochromatic region. The binary partial image and the position, size, and color of the area are output.

FIG. 2 shows an example of a hardware configuration for realizing the monochromatic area extracting unit 102. In FIG. 2, 21 is a CP
U and 22 are disk devices, and 23 is a disk I / O, which controls the interface with the hard disk 22. 24 is a ROM for storing control programs executed by the CPU 21; 25 is an I / O (input / output) port;
Is a RAM (random access memory), which is used as a work area when the CPU 21 executes processing and holds various data. A bus 27 connects the blocks. Although the same hardware configuration is used in other units described later, the same device may be shared with the other units.

The CPU 21 extracts a single color area in the following procedure of the single color area extraction processing. For example, when the color image shown in FIG. 3 (including characters and figures of different colors) is input, the table shown in FIG. 4 (referred to as a monochromatic area table 41) and the binary partial images 42 to 42 corresponding to each monochromatic area are displayed. 46
Is output. Here, each line of the monochrome region table 41 is
It corresponds to each monochrome region included in the color image. In the column direction of the monochrome region table 41, the position and size of the circumscribed rectangle of the region, the color of the region, the number of pixels included in the region, and the index to the binary partial image indicating the monochrome region (address of the binary partial image or A number indicating a binary partial image) is written. For example, here, the position and size of the circumscribed rectangle of the area are represented by the upper left (x, y) coordinates of the rectangle and the position by the width and height thereof. Here, the circumscribed rectangle of the area corresponds to the position and size of the binary partial image. The color of each area is RG.
Although it is represented by B value, in addition to this, CMY, HSI,
It may be represented by a known color coordinate system such as L ^* a ^* b ^* , L ^* u ^* v ^* . In FIGS. 3 and 4, the color (color 1) of the area number “1” is RGB = (50,128,6).
0), the color of the area number “2” (color 2) is RGB = (15
8, 149, 30).

[Monochromatic Region Extraction Processing Procedure] The processing procedure of the monochromatic area extraction unit 102 will be described. Monochromatic area extraction unit 10
In No. 2, the monochrome array label array is used as temporary data, the monochrome area table 41 and the output binary image are used as output data, and they are placed on the RAM 26. This single color area label array has the same size as the input color image, and each element of the single color area label array corresponds to a pixel at the same position in the input color image. The number of the area to which the pixel belongs (number is assigned to each area, and this is referred to as area number) is written in this single-color area label array.

FIG. 5 shows the CPU 21 of the monochromatic area extracting unit 102.
The control program for executing this process is stored in the ROM 24. Hereinafter, each step of the flowchart will be described.

First, in step S1, R required for processing is set.
The data area of the AM 26 is initialized. Below, step S
It is determined that the raster scanning is completed in step 3 (step S3).
Until the determination is positive), the process from step S4 to step S11 is performed for each pixel of the input color image (the one on the disk device 22 is input through the disk I / O 23 or the RAM 26). The scanning order is repeated (step S2). Here, the target pixel being processed is called a target pixel. In addition, a target area that has already been registered in the single-color area table 41 and has been confirmed as to whether the target pixel is included in that area will be referred to as a comparison area.

In the following, if it is found in step S8 that the pixel of interest is not included in the registered area (processing of all pixels in the target area ends: if the determination in step S8 is affirmative), or In step S10, a region to which the pixel of interest belongs is found (when the determination in step S10 is affirmative).
Up to step S8 to step S11 are repeated until it is confirmed whether or not the pixel of interest belongs to all the areas registered in the monochrome area table 41.

In step S9, the color difference between the color of the pixel of interest and the color of the comparison area is calculated. A known calculation method is used to calculate the color difference. For example, if you are using a RGB color ^{coordinates, (R-R0) 2 +} (G-G0) 2 + (B-B0) 2 R, G, B are the RGB values of the target pixel R0, G0, B0 comparison can be used formula for RGB values of area, if you are using the L ^* a ^* b ^* color ^{coordinates, (L * -L * 0)} 2 + (a * -a * 0) 2 + ( b ^* -b ^* 0) ² L ^* , a ^* , b ^* are L ^* a ^* b ^* values of the pixel of interest L ^* 0, a ^* 0, b ^* 0 are L ^* a ^* b ^* values of the comparison area. It can be calculated using a calculation formula.

In step S10, the color difference calculated in step S9 is compared with a preset threshold value (stored in the ROM 24 or set in the RAM 26 at the time of starting the process). When the color difference is larger than the threshold value (when the determination in step S10 is negative), the comparison area is set as the next candidate area in the monochrome area table 41 (step S10).
6) and returns to step S8. On the other hand, in step S10,
When the color difference is smaller than the threshold value (when the determination in step S10 is affirmative), it is determined that the pixel of interest belongs to the comparison area, and the process proceeds to step S11.

In step S11, the pixel of interest is added to the comparison area and the single color area table 41 is updated. That is, the color (average value) and the number of pixels of the comparison area are recalculated by adding the target pixel.

In step S4, the region number of the comparison region is written in the element corresponding to the pixel of interest in the monochrome region label array (represented by the region number of the monochrome region), and the process proceeds to steps S2 and S3.

Steps S8 to S11 are repeated, and when there are no comparison area candidates in step S8 (when the determination in step S8 is affirmative), that is, in the area registered in the monochromatic area table 41, the pixel of interest is If there is no region to which the pixel belongs, the process proceeds to step S7, and the pixel of interest is set as a pixel of the new region, and the monochrome region table 41
Register with. Thus, steps S4 to S11
When all pixels of the input color image are processed (when the determination in step S3 is affirmative), the process proceeds to step S12. In step S12, the circumscribing rectangle of the region consisting of elements having the same region number in the monochrome region label array is calculated, and a binary partial image having the position and size of the circumscribing rectangle is generated. Then, in the single color area label array, the pixels of the binary partial image corresponding to the portion having the target area number are black pixels and the other pixels are white pixels.

The monochromatic area extracting unit 102 outputs the monochromatic area table 41 and the binary partial image on the RAM 26, which are generated by these processes (outputs to the disk device 22 through the disk I / O 23 if necessary). .

<Multiple Outline Extraction Unit 103> Next,
The multiple outline extraction unit 103 includes a single color region extraction unit 10
A rough contour vector is extracted from the binary partial image of the raster scanning format corresponding to each monochromatic area output from No. 2. For example, using the examples of FIG. 3 and FIG.
The monochromatic area table 41 and the binary partial images 42 to 4 shown in FIG.
The rough contour vectors 62 to 66 extracted from No. 6 are output.

FIG. 7 is a block diagram showing the structure of the plural outline extracting section 103.

The multiple outline extraction unit 103 has an outline extraction control unit 31 and an outline extraction unit 32, and the outline extraction control unit 31 is equivalent to the hardware configuration sequence realizing the single color area extraction unit 102 shown in FIG. It consists of the hardware configuration of. Of course, the same hardware as the single color area extraction unit 102 may be shared. Here, the hardware configuration example shown in FIG. 2 will be described.

[Multiple Outline Extraction Processing] FIG. 8 shows a processing procedure of the plural outline extraction processing by the CPU 21 (the processing of step S25 is performed by the outline extraction unit 32). Hereinafter, the multiple outline extraction process will be described with reference to FIG.

In step S21, temporary data on the RAM 26 (variables indicating the area currently being processed)
To initialize. Hereinafter, it is determined that there is no region to be processed in step S23 while changing the target region in step S22 (when the determination in step S23 is affirmative).
Until step S24 to step S26 are repeated. In step S24, the binary partial image of each area is extracted from the single-color area table 41 and passed to the outline extraction unit 32 in the raster format via the RAM 26 or the disk device 22. In step S25, the outline extraction unit 32
At, the rough contour vector of the input binary partial image is extracted and passed to the outline extraction control unit 31 via the RAM 26 or the disk device 22. In step S26,
The outline extraction control unit 31 registers the rough contour vector in the single color area table 41.

In the plural outline extraction processing, after all the above steps are completed, the rough contour vector and the monochromatic area table 41 on the RAM 26 are output (output to the disk device 22 through the disk I / O 23 if necessary). .

The outline extraction unit 32 was previously filed by the applicant of the present application (Japanese Patent Application No. 2-28195).
8, filed October 22, 1990). Next, the outline extraction unit 32 described in Japanese Patent Application No. 2-281958 will be briefly described.

FIG. 9 shows the scanning mode of the raster scanning type binary partial image data output from the outline extraction control section 31, and the scanning of the raster scanning type binary partial image data input by the outline extraction section. The morphology is also shown. Outline extraction control unit 31 in a format like this
The outline extraction unit 32 inputs the binary partial image data output by. In FIG. 9, reference numeral 91 denotes a certain pixel (target pixel) of the binary partial image being raster-scanned, and 92 denotes a 9-pixel area including 8 pixels in the vicinity of this pixel 91. The aforementioned Japanese Patent Application No. 2-2819
The outline extraction unit 32 described in 58 moves the position of the target pixel 91 in the raster scanning order, and for each target pixel,
The contour vector (horizontal vector or vertical vector) existing between the target pixel 91 and the eight pixels adjacent to the target pixel is determined according to the state of each pixel (white pixel or black pixel) in the 9-pixel region indicated by 92. It is detecting. Then, when a contour vector exists, the rough contour vector is extracted while extracting the starting point coordinates and the orientation data of the side vector and updating the connection relationship between the side vectors.

FIG. 10 is a diagram showing an example of the extraction state of the contour vector between the target pixel 91 and neighboring pixels of the target pixel 91.

In the figure, the mark Δ indicates the starting point of the vertical vector, and the mark ◯ indicates the starting point of the horizontal vector.

FIG. 11 shows an example of the rough contour vector loop extracted by the outline extracting section 32.
Here, each square separated by a grid shows a pixel position of the input image, a blank square means a white pixel, and a black circle indicates a black pixel. Here, as in FIG. 10, Δ represents the starting point of the vertical vector, and the ∘ mark represents the starting point of the horizontal vector.

As can be seen from the example of FIG. 11, the outline extraction unit 32 extracts a region in which black pixels are connected as a rough contour vector loop in which horizontal vectors and vertical vectors are alternately continuous, and sets the direction in which the vector advances. The vector is extracted so that the right side is a black pixel area.

The starting point of each rough contour vector is extracted as the intermediate position of each pixel of the input image, and the line portion of one pixel width in the original image is also extracted as a rough contour loop having a significant width. The rough contour vector loop group thus extracted is output in a data format as shown in FIG. That is, the total rough contour data number a extracted from the image and the first
Each of the rough contour loop data is composed of data representing each of the rough contour loop data groups from the contour loop to the a-th contour loop, and each rough contour loop data is the total number of starting points of the contour vector existing in the rough contour loop (also considered as the total number of contour side vectors. Can be done)
And a sequence of the starting point coordinates (x coordinate value, y coordinate value) of each contour side vector (the starting point of the horizontal vector and the starting point of the vertical vector are alternately arranged) in the order that constitutes the loop. ing.

<Multiple outline smoothing / magnifying unit 104>
Next, the multiple outline smoothing / scaling unit 104 smoothes and scales the rough contour vector data in the form of vector data. For example, to explain with the example of FIG. 6, the monochrome region table 41 and the rough contour vectors 62 to 66 of FIG.
, And outputs contour vectors 132 to 136 obtained by smoothing and scaling the monochromatic region table 41 and the rough contour vectors 62 to 66 shown in FIG. 13, respectively.

FIG. 14 shows a plurality of outline smoothing / magnifying units 1.
It is a block diagram which shows the structure of 04.

The plurality of outline smoothing / magnifying units 104 are
It has an outline smoothing / scaling control unit 141 and an outline smoothing / scaling unit 142. The outline smoothing / magnification control unit 141 is, for example, the monochrome region extraction unit 1 shown in FIG.
02 is configured with a hardware configuration equivalent to the hardware configuration example. Of course, the same hardware as the single color area extraction unit may be shared. Here, description will be given using the hardware configuration example of FIG.

[Multiple outline smoothing / magnifying processing] FIG.
5 shows the procedure of multiple outline smoothing / magnifying processing. Hereinafter, a plurality of outline smoothing / scaling processes of the CPU 21 (step S35 is performed by the outline smoothing / scaling 142) will be described with reference to FIG.

In step S31, temporary data on the RAM 26 (variables indicating the area currently being processed)
Initialize the area. Hereinafter, while changing the target area in step S32, steps S34 to S36 are repeated until it is determined in step S33 that there is no processing target area (when the determination in step S33 is affirmative). In step S34, the rough contour vector of each area is extracted from the single color area table 41, and the outline smoothing / magnifying unit 1 is executed via the RAM 26 or the disk device 22.
Pass to 42. In step S35, the outline smoothing /
In the scaling unit 142, the input rough contour vector is smoothed / scaled to create a contour vector, and the outline smoothing / scaling control unit 1 is executed via the RAM 26 or the disk device 22.
Pass it to 41. In step S36, the outline smoothing /
The scaling control unit 141 registers the contour vector in the monochrome region table. Also, the position (x coordinate, y coordinate) and size (width, width,
Height), the value of the number of pixels (described later), and the magnification setting unit 161.
Multiply the magnification set by (FIG. 16).

In the plural outline smoothing / magnifying processing, after all the above processing is completed, the contour vector on the RAM 26 and the monochromatic area table 41 are output (if necessary, output to the disk device 22 through the disk I / O 23). ).

The outline smoothing / magnifying unit 142 is, for example, Japanese Patent Application No. 3-345 previously filed by the present applicant.
062. Below, Japanese Patent Application No. 3-
345062 outline smoothing / magnifying unit 142
Will be briefly described.

FIG. 16 shows an outline smoothing / magnifying unit 14
2 shows the configuration.

In FIG. 16, reference numeral 161 is a magnification setting unit for setting a magnification, and 162 is a first smoothing and scaling unit, which smoothes the input rough contour data with the magnification set by the magnification setting unit 161. And perform scaling processing. The result processed in this way is further smoothed by the second smoothing unit 163 to be the final output.

The variable magnification setting section 161 changes the fixed value preset by the dip switch or dial switch,
It may be passed to the first smoothing / magnifying unit 162, or may be in a form such as being provided from the outside via an I / F (interface), and the main scanning is performed for the image size given as an input. This is a section that gives information on how many times to multiply in the (horizontal) direction, the sub-scanning (vertical) direction, and independently.

The first smoothing / magnifying section 162 obtains magnification information from the magnification setting section 161, and performs smoothing / magnifying processing.
The first smoothing process in the first smoothing / magnification changing unit 1162 is performed for each closed loop unit of the rough contour data. Focusing on each contour edge (horizontal vector or vertical vector) vector of each rough contour data in turn, up to three vectors before and after each vector for each contour edge (i.e. (3), the target side itself, and a total of three after the target side, and up to a maximum of seven side vectors). For each of these patterns, the contour points after the first smoothing that are the first smoothing results for the target side are defined. Then, the coordinate value of the contour point after the first smoothing and additional information indicating whether the contour point is a corner point (hereinafter referred to as corner point information) are output.
Here, the contour points after the first smoothing, which are not determined as the corner points, are further smoothed by the second smoothing later.

FIG. 17 shows this state, that is, the target rough contour edge vector Di, the three edge vectors Di-1, Di-2, Di-3 before the target rough contour edge vector and the target rough contour edge vector. The state of the following three edge vectors Di + 1, Di + 2, Di + 3 and the state of the contour points after the first smoothing defined for the target edge Di are shown.

In the second smoothing, the data after the first smoothing is input. That is, the number of closed loops, the number of contour points for each closed loop, the coordinate value data string of the first smoothed contour points for each closed loop, and the additional information data string input of the first smoothed contour points for each closed loop. Then, the contour point data after the second smoothing is output. The contour data after the second smoothing is shown in FIG.
As shown in, the number of closed loops (N), the contour point number table (Li) for each closed loop, and the coordinate data sequence (Xi, Yi) of the second smoothed contour points for each closed loop.

Similar to the first smoothing, the second smoothing is processed for each contour loop unit, and the processing is advanced for each contour point in each contour pull. For each contour point, if the focused contour point is a corner point, the input contour point coordinate value itself is used as the second smoothed contour point coordinate data for that focused contour point. When the contour point of interest is a non-angular point, the second smoothing for the contour point of interest is performed using the value obtained by the weighted average of the coordinate values of the contour points before and after and the coordinate value of the contour point of interest. Use the contour point coordinate values that have already been set.

<Color Image Reproducing Unit 105> Next, in the color image reproducing unit 105, the contour vector is output from the contour vectors output from the plurality of outline smoothing / magnifying units 104 and the color of the region stored in the monochrome region table 41. A color image in a raster scanning format having an area having a shape represented by a vector is reproduced.

FIG. 19 is a block diagram showing the arrangement of the color image reproducing section 105. The color image reproduction unit 105 is 2
A value image reproduction unit 51, a color image reproduction control unit 52, and an image memory 53 are provided. The binary image reproducing unit 51 is provided in Japanese Patent Application No. 3-172098, Japanese Patent Application No. 3-172097, or Japanese Patent Application No. 3-1720 previously filed by the present applicant.
2099 has a configuration similar to that of the apparatus described in 2099, inputs the contour vector output from the plurality of outline smoothing / variable-magnification units 104, creates a vector graphic represented by the contour vector, and defines an area surrounded by the vector graphic. It is possible to generate a binary image by painting and output it in raster scanning order.

The color image reproduction control unit 52 has a hardware configuration equivalent to that of the hardware configuration example for realizing the monochrome region extraction unit 102 shown in FIG. Of course, the same hardware as the single color area extraction unit may be shared. Here, description will be given using the hardware configuration example of FIG.

The image memory 53 is composed of a known storage device (memory or the like) capable of holding an image, but the RAM 26 of the color image reproduction controller 52 or the disk device 22 may be used.

[Color Image Reproduction Processing] FIG. 20 is a flowchart showing the processing procedure performed by the CPU 21 (the step S2005 is performed by the binary image reproduction unit 51) of the color image reproduction processing. The color image reproduction process will be described below with reference to FIG.

First, in step S41, the RAM 26
Initialize the above temporary data area (such as a variable indicating the area currently being processed). Hereinafter, while changing the target area in step S42, it is determined in step S46 that there is no processing target area. Until the determination in step S43 is positive), steps S44 to S46 are repeated. As a result, each monochromatic area is converted into the image memory 53
Overwriting. In step S44, the contour vector of each area is extracted from the monochrome area table 41 and passed to the binary image reproducing unit 51. In step S45, the binary image reproduction unit 51 reproduces the binary image from the input contour vector, and outputs the binary image to the color image reproduction control unit 52 in the raster scanning order. In step S46, the following is sequentially performed in the raster scanning order with respect to the rectangular portion on the image memory 53, which is indicated by the position and size of the (currently noticed) region described in the monochrome region table 41.

First, when the output data from the binary image reproducing section 51 is "1", the color of the area registered in the monochromatic area table 41 is written in the image memory 53 and output from the binary image reproducing section 51. If the data is "0", nothing is written in the image memory 53.

Next, in step S43, if it is determined that the processes in steps S44 to S46 have been completed for all the areas (if the determination in step S43 is affirmative), the process advances to step S47 to copy the color image in the image memory 53. Output in raster scan order.

<Color Image Output Unit 106> Next, the color image output unit 106 displays the color image data of the raster scanning format output from the color image reproducing unit 105, makes a hard copy, or uses the communication path. Or output to. These are configured by known color image output devices.

[Second Embodiment] By providing a variable length data creating unit 107 and an outline output unit 108 as shown in FIG. 21 after the plural outline extracting unit 103 in the description of the first embodiment, the rough contour is obtained. It can also be used as a vector storage or communication device.

The variable length data creating section 107 inputs the rough contour vector and the monochromatic area table 41, and converts the rough contour vector into a variable length format expression, thereby reducing the data amount of the rough contour vector. Here, the variable-length format rough contour vector expresses the difference between the starting point coordinates of the attention vector and the starting point coordinates of the vector continuous to the attention vector as variable-length format data. I will call it. Variable length data creation unit 107
Outputs variable length data and a single color area table. For example, when the monochromatic area table 41 and the rough contour vector shown in FIG. 6 are input, the variable length data 221 to 22 shown in FIG.
6 and the monochromatic area table 41 are output.

The outline output unit 108 stores the variable length data and the single color area table output by the variable length data creation unit 107 in a storage device such as a magnetic disk or via a facsimile modem or a network I / F. It is sent to an external communication device.

As shown in FIG. 23, the variable length data creation unit 107 includes a variable length data creation control unit 71 and a vector data creation unit 72 described in Japanese Patent Application No. 4-152461 filed by the present applicant. Have The variable length data creation control unit 71 is, for example, the single color area extraction unit 102 shown in FIG.
The hardware configuration is the same as the hardware configuration example for realizing Of course, the same hardware as the single color area extraction unit 102 may be shared. Here, it demonstrates using FIG. The vector data creation unit 72 described in Japanese Patent Application No. 4-152461 takes a rough contour vector as an input, calculates the difference between the starting point coordinates of the vector of interest and the starting point coordinates of the vector continuous to the vector of interest, and sets the value to a variable length. Express.

The outline output unit 108 is composed of a known storage device or communication device.

[Variable Length Data Creation Processing] FIG.
It is a flowchart which shows the procedure of the variable length data creation process performed by U21 (step S55 is implemented by the vector data creation part 72). The variable length data creation process will be described below with reference to FIG.

In step S51, temporary data on the RAM 26 (variables indicating the area currently being processed)
Initialize the area. Hereinafter, while changing the target region in step S52, steps S54 to S56 are repeated until it is determined in step S53 that there is no target region (when the determination in step S53 is positive). In step S54, the rough contour vector of each area is extracted from the single color area table 41 and passed to the vector data creation unit 72 via the RAM 26 or the disk device 22. In step S55, the vector data creation unit 72
In, convert the rough contour vector to variable length data,
It is output via the AM 26 or the disk device 22. In step S56, the variable length data creation unit 72
The variable length data is registered in the single color area table 41.

In the variable length data creation process, after all the above processes are completed, the variable length data on the RAM 26 and the monochromatic area table 41 are output (if necessary, the disk I / I).
Output to the disk device 22 through O23).

The variable length data stored or transmitted by the outline output unit 72 is the same as Japanese Patent Application No. 4-152461.
It is possible to convert to a rough contour vector by using a part of the function of the outline smoothing / scaling unit described, and after converting to the rough contour vector, input to the plurality of outline smoothing / scaling units 104 in the first embodiment. It doesn't matter.

[Third Embodiment] In the above description of the first embodiment, the monochromatic region binarization unit 102 uses the recursive threshold method (structuring of color image information by region division processing, information processing,
Vol.19, No.12, Dec, 1978, pp.1130-1136) or a method using limited color representation method (1990 IEICE Spring National Convention D416 7-168). You may use and extract a monochrome area. For example, the recursive threshold method can be applied to RGB, HSI, YI for color images.
The process of determining the region division threshold value from the valley of the histogram in the Q color feature and cutting out the region is recursively repeated for each of the cut out regions. By the above operation, the same result as the single color area label array obtained by the single color area binarization processing can be obtained. After performing the above operation, the steps after step S12 of the monochrome region binarization processing are executed from the clipped region to create a binary partial image, and the average color in the region is calculated to calculate the monochrome region table 41. The same effect as that of the monochromatic region binarization process can be obtained by writing in

[Fourth Embodiment] In the description of the first embodiment, the monochromatic region extracting unit 102 is provided with a monochromatic region specifying unit 109 as shown in FIG. 25, and the following monochromatic region extracting process is performed. It doesn't matter. This monochromatic area designating section 10
Reference numeral 9 comprises a known display capable of displaying a color image and a known pointing device such as a mouse or a trackball. In this embodiment, the user is requested to specify a part of the monochrome area in advance. A single color area is extracted based on the data. As a result, it is possible to realize monochromatic region extraction that more closely matches the user's feeling.

[Monochromatic Region Extraction Processing Procedure] The processing procedure of the monochromatic area extraction unit 102 in the fourth embodiment will be described.
In the monochromatic area extracting unit 102, as in the first embodiment, the color image on the RAM 26 or the disk device 22 is input, the monochromatic area label array is provided as temporary data on the RAM 26, and the monochromatic area table 41 is provided as output data.
And the output binary image.

FIG. 26 shows a processing flowchart of the single color area extraction processing in the fourth embodiment. Below, this CPU2
The monochrome region extraction process will be described with reference to the process flowchart executed in 1.

In step S61, the monochromatic area designating unit 109 is used.
In, the input image is displayed on the display, and the user uses the pointing device to specify a part (one point, a plurality of points, a region, etc.) in the monochrome region. Then step S6
In step 2, a data area on the RAM 26 required for processing is initialized. In step S63, the user registers the designated area in the monochrome area table 41 (writes the average color of the portion designated by the user in the monochrome area table 41) in step S61.

Thereafter, the processes of steps S65 to S68 are repeated for each pixel of the input color image in the raster scanning order until it is determined in step S65 that the raster scanning is completed (when the determination in step S65 is affirmative). Perform (step S64). Here, the pixel being processed is referred to as a pixel of interest).

In step S66, the color difference between the pixel of interest and each area registered in the monochromatic area table 41 is calculated, and the area having the smallest color difference is obtained. In step S67, the pixel of interest is added to the region obtained in step S66, and the monochrome region table 41 is updated. In step S68,
The area number of the comparison area is written in the element for the pixel of interest in the array area, and the process proceeds to step S64. In this way, steps S66 to S68 are repeated, and when the processing is completed for all pixels of the input color image, step S6
Proceed to 9. In steps S69 and S70, the same processing as in the first embodiment is performed.

The fourth embodiment may have the same configuration as that of the third embodiment.

The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of a single device. Further, the present invention can be applied to the case where it is achieved by supplying a system or apparatus with a program for implementing the present invention.

As described above, according to this embodiment, an outline vector is extracted from a color image composed of limited colors, and smoothing and scaling processing is performed in the state of the extracted outline vector expression, and the smoothing is performed. By reproducing the color image from the scaled outline vector, it is possible to obtain a high quality image which is scaled to an arbitrary magnification independently in the main scanning direction and the sub-scanning direction. .

Further, the amount of communication data can be reduced by storing or communicating in the state of the outline vector expression extracted from the color image.

[0088]

As described above, according to the present invention, a monochrome area in a color image is extracted, contour line information of the extracted monochrome area is obtained, and a high quality color image based on the contour information is obtained. Smoothing and scaling can be performed.

Further, the present invention has the effect that the image data can be scaled while reducing the amount of image data and maintaining high image quality.

[0090]

[Brief description of drawings]

FIG. 1 is a functional block diagram showing a functional configuration of an image processing apparatus according to an embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration example of a monochrome region extraction unit of the present embodiment.

FIG. 3 is a diagram showing an example of a color image targeted by the present embodiment.

FIG. 4 is a schematic diagram of data output from a monochrome region extraction unit of this embodiment.

FIG. 5 is a flowchart showing a monochrome region extraction process of this embodiment.

FIG. 6 is a schematic diagram of output data of a plurality of outline extraction units of this embodiment.

FIG. 7 is a block diagram showing a configuration of a plurality of outline extraction units of this embodiment.

FIG. 8 is a flowchart showing a plurality of outline extraction processing according to the present embodiment.

FIG. 9 is a diagram illustrating a manner of extracting a rough contour vector from a raster scanning binary image.

FIG. 10 is a diagram illustrating a mode of extracting a rough contour vector from a raster scanning binary image.

FIG. 11 is a diagram illustrating a manner of extracting a rough contour vector from a raster scanning binary image.

FIG. 12 is a diagram showing the form of a rough contour vector output from the outline extraction unit of the present embodiment.

FIG. 13 is a schematic diagram of output data of a plurality of outline smoothing / magnifying units according to the present embodiment.

FIG. 14 is a block diagram showing a configuration of a plurality of outline smoothing / magnifying units according to the present embodiment.

FIG. 15 is a flowchart showing a plurality of outline smoothing / magnifying processing of this embodiment.

FIG. 16 is a block diagram showing a configuration of an outline smoothing / magnifying unit according to the present embodiment.

FIG. 17 is a diagram for explaining the processing operation of the first smoothing.

FIG. 18 is a morphological view of contour data after second smoothing.

FIG. 19 is a block diagram showing a configuration of a color image reproducing unit according to the present embodiment.

FIG. 20 is a flowchart showing a color image reproduction process in this embodiment.

FIG. 21 is a functional block diagram showing a functional configuration of the image processing apparatus of the second embodiment of the present invention.

FIG. 22 is a diagram for explaining the output of the variable length data creation unit in the second embodiment.

FIG. 23 is a block diagram showing the configuration of a variable length data creation unit of the second embodiment.

FIG. 24 is a flowchart showing a variable length data creation process of the second embodiment.

FIG. 25 is a functional block diagram showing a functional configuration of an image processing apparatus according to a fourth embodiment of the present invention.

FIG. 26 is a flowchart showing a monochrome region extraction process in the fourth embodiment.

[Explanation of symbols]

 31 Outline Extraction Control Section 32 Outline Extraction Section 41 Monochromatic Area Table 51 Binary Image Reproduction Section 52 Color Image Reproduction Control Section 53 Image Memory 71 Variable Length Data Creation Control Section 72 Vector Data Creation Section 101 Color Image Acquisition Section 102 Monochromatic Area Extraction Section 103 Outline Extracting Unit 104 Outline Smoothing / Scaling Unit 105 Color Image Reproducing Unit 106 Color Image Output Unit 107 Variable Length Data Creating Unit 108 Outline Outputing Unit 109 Single Color Area Designating Unit 141 Outline Smoothing / Scaling Control Unit 142 Outline Smoothing / Scaling Unit Part 161 Magnification setting part 162 First smoothing / magnifying part 163 Second smoothing part

Continuation of the front page (51) Int.Cl. ⁶ Identification number Office reference number FI technical display location G06F 15/68 310 A

Claims (12)

[Claims] 1. An image processing method for expressing a monochrome region of a color image by a color of the region and vector coordinates representing a boundary of the region, wherein a monochrome region extracting step of extracting a color and a shape of the monochrome region from the color image. And a step of extracting vector coordinates representing a boundary line of the monochrome region from the shape of the extracted monochrome region. 2. The method according to claim 1, further comprising the steps of smoothing the shape of the monochrome region and scaling the shape of the monochrome region based on vector coordinates representing a boundary line of the monochrome region.
The image processing method described in. 3. A step of converting vector coordinates representing a boundary line of the single color area into a variable length format, and a step of outputting the color image using the vector coordinates of the variable length format and the color of the single color area. The image processing method according to claim 1, further comprising: 4. A step of reproducing a color image from the vector coordinates of the boundary line of the monochrome area and the color of the monochrome area,
The image processing method according to claim 1, further comprising the step of outputting the reproduced color image. 5. The monochromatic region extracting step extracts pixels having a color difference of not more than a threshold value as a monochromatic region by raster-scanning an input color image, and the shape of the monochromatic region is a circumscribed rectangle that circumscribes the monochromatic region. The image processing method according to any one of claims 1 to 4, wherein the color image and the number of pixels of the monochromatic area, and the size and position of the circumscribing rectangle are output together with outputting as a value image. 6. The monochromatic region extracting step includes a step of designating a monochromatic region, extracting pixels whose color difference from a portion of the designated monochromatic region is a threshold value or less as the same monochromatic region, and extracting the shape of the monochromatic region. The binary image of a circumscribing rectangle circumscribing the monochromatic region is output, and the color and the number of pixels of the monochromatic region and the size and position of the circumscribing rectangle are output. The image processing method according to item 1. 7. The color image is reproduced by creating a color image in which only the single color areas are reproduced from the vector coordinates of the color and the boundary for each single color area, and the size and position information of the circumscribing rectangle of each single color area is created. The image processing method according to claim 4, which is performed by superimposing the color images with each other. 8. An image input unit for inputting a color image, a monochrome region extracting unit for extracting a color and a shape of a monochrome region in the color image inputted from the image input unit, and an monochrome region extracting unit for extracting the color and shape. An image processing device, comprising: vector extraction means for extracting vector coordinates representing a boundary of the monochrome region based on the shape of the monochrome region. 9. The apparatus further comprises vector smoothing / magnifying means for smoothing the shape of the monochromatic area and scaling the shape based on the vector coordinates representing the boundary obtained by the vector extracting means. Item 8. The image processing device according to item 8. 10. A variable-length data creating unit that converts the vector coordinates representing the boundary obtained by the vector extracting unit into a variable-length format, and a variable-length format vector coordinate expression obtained by the variable-length data creating unit. 9. The image processing apparatus according to claim 8, further comprising an output unit that outputs the color image using the color of the single color region obtained from the single color region extraction unit. 11. A color image reproducing unit for reproducing a color image from the vector coordinate expression obtained by the vector smoothing / magnifying unit and the color of the single color region obtained from the single color region extracting unit, and the color image. The image processing apparatus according to claim 9, further comprising a color image output unit that outputs the color image reproduced by the reproducing unit. 12. The image processing apparatus according to claim 8, wherein the monochrome region extraction unit further includes a designation unit that designates a monochrome region.