JP2001144954A - Image processing unit and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve a problem of a conventional image processing unit where deterioration in image quality has been remarkable in a reproduced image because there are extracted parts and non-extracted parts in one character when thick parts and thin parts are in existence in the character in the image area separation and because a block-shaped image pattern may be wrongly extracted on the occurrence of mis-extraction in the image patterns. SOLUTION: First a shadow extract section 11 extracts an area with high gray level from input image data, a dot extract section 12 extracts an area consisting of dots, and a line segment extract section 13 extracts line segments with a width by a 1st prescribed number of pixels. Then a small area extract section 14 extracts an area with a width by a 2nd prescribed number of pixels from each area extracted by the shadow extract section 11 and the dot extract section 12, and a line segment correction section 15 corrects the line segments extracted by the line segment extract section 13 on the basis of the extracted 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 apparatus such as a copying machine or a facsimile, and a processing method therefor.
The present invention relates to an image processing apparatus and an image processing method that separate and perform image processing suitable for each area.

[0002]

2. Description of the Related Art In an image processing apparatus such as a copying machine or a facsimile, when an input image includes a character area such as a character or a line drawing and a picture area such as a photograph or a picture,
When reproducing the image, it is desirable from the viewpoint of image quality to separate the character area from the picture area, and to perform the processing emphasizing the resolution on the character area and the processing emphasizing the gradation on the picture area. Also in the case of transmitting the image data as described above, it is desirable to separate the character area and the picture area and to perform compression processing on each of them by different methods from the viewpoint of image quality and compression ratio.

[0003] Specifically, an image read by a scanner or the like, or transmitted by facsimile or the like,
When making a hard copy of an image containing a mixture of characters, line drawings, photos, and halftone dots, processing that emphasizes resolution is applied to character regions such as characters and line drawings, and to image regions such as photos and halftone dots. By performing the process with emphasis on gradation, a high-quality reproduced image can be obtained.

When an image including characters, line drawings, photographs, halftone dots, and the like is transferred to an image output device at a remote place via a network, a character area and a picture area are separated from each other. On the other hand, when the compression processing is performed by a different method, high-quality and small-capacity image data can be obtained, so that a high-speed transfer speed and high-quality reproduced image can be obtained.

Here, in order to adaptively process the above-described processing with emphasis on resolution and gradation, depending on each area of an image, it is necessary to accurately separate a character area and a picture area included in the image. is there. Hereinafter, the separation between the character area and the picture area is referred to as image area separation. Regarding this image area separation,
Conventionally, various proposals have been made.

For example, an image is divided into blocks of a certain size, the maximum density and the minimum density of the pixels included in each divided block are determined, and the difference between the maximum density and the minimum density is determined in advance. In comparison with the threshold, a block larger than the threshold is determined as a character area, and a block smaller than the threshold is determined as a picture area (hereinafter referred to as a first related art), or a local operator (filter) centering on a pixel of interest. There is a method of comparing a filtering result with a predetermined threshold, and determining a pixel larger than the threshold as a character area pixel and a pixel smaller than the threshold as a picture area pixel (hereinafter, referred to as a second conventional technique).

Further, as described above, instead of performing image area separation using only one of the first and second prior arts, processing for extracting a character area or processing for extracting a picture area is performed. (Hereinafter, referred to as a third conventional technique) in which a plurality of processes such as the above are performed, and an image area is separated from each processing result with high accuracy.
Has also been proposed (see JP-A-2-294885). This third prior art will be briefly described with reference to FIG.

In FIG. 27, the input image signal is
It is supplied to a character extracting unit 201, a halftone dot extracting unit 202, and a contour extracting unit 203. The character extracting unit 201 determines a character area on a pixel-by-pixel basis from an input image signal, and outputs a result of the determination. The dot extracting unit 202 determines a dot area for each pixel and outputs a result of the determination. The determination results of the character extraction unit 201 and the halftone dot extraction unit 202 are supplied to the erroneous determination removal unit 205 after the logical sum operation unit 204 performs a logical sum operation for each pixel. Misjudgment removal unit 2
At 05, the character extraction result is corrected.

Next, the erroneous judgment removing unit 205 and the contour extracting unit 2
Each output result of 03 is supplied to the contour regenerating unit 207 after the logical product operation is performed by the logical product operation unit 206 on a pixel basis. In the contour regenerating section 207, the contour of the character / line image is corrected for the result of the logical product operation of the logical product calculation section 206. Then, by using the output result of the contour regeneration unit 207 as an image area separation result, highly accurate image area separation can be performed.

[0010]

However, in the case of the first prior art, since the image area separation is performed in block units, the image area determination result of the outline portion of the character / line drawing is faithful to the input image. It is not. Further, in the case of the second prior art, since it is a method of extracting an edge contained in an image, there is a problem that it is easy to extract noise or an edge contained in a picture.

On the other hand, in the case of the above third prior art, there are few erroneous extractions of edges in a picture, and the outline of a character or a line drawing has an extraction result faithful to an input image. Method. However, the following problems still remain. In the case of a bold character / bold line, only the outline is extracted, and it is difficult to extract the inside of the character / line. When a wide part and a narrow part exist in one character, there are parts that are not extracted and parts that are not extracted. When erroneous extraction occurs in a picture, erroneous extraction in a block shape may occur, and when an image is reproduced, image quality deterioration is more conspicuous.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems of the prior art, and it is an object of the present invention to faithfully extract a character or a line drawing from an input image and to extract a character / line drawing from a pattern area. It is an object of the present invention to provide an image processing apparatus and an image processing method capable of performing high-accuracy image area separation processing without causing erroneous extraction.

[0013]

According to the present invention, there is provided an image processing apparatus comprising: an input unit for inputting image data; a shadow extracting unit for extracting an area having a high density from the image data input by the input unit; Halftone dot extracting means for extracting an area composed of halftone dots from input image data, line segment extracting means for extracting a line segment having a width of a first predetermined number of pixels from input image data, A small region extracting unit for extracting a region having a width of a second predetermined number of pixels from the region extracted by the extracting unit and the region extracted by the halftone dot extracting unit, and a region extracted by the small region extracting unit. A line segment correction unit that corrects the line segment extracted by the line segment extraction unit based on the area.

In the image processing apparatus having the above configuration, first,
The input means inputs image data to the shadow extracting means, the halftone dot extracting means, and the line segment extracting means. Then, the shadow extracting means extracts a region having a high density from the input image data, the halftone extracting means extracts an area composed of halftone dots from the input image data, and outputs each extraction result to a small area extracting means. Give to. Then, the small area extracting means extracts an area having a width equal to the second predetermined number of pixels from the extraction results, and provides the extraction result to the line segment correcting means. Then, the line segment correction unit corrects the line segment extracted by the line segment extraction unit based on the region extracted by the small region extraction unit.

[0015]

Embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is a block diagram showing an outline of a basic configuration of an image processing apparatus according to the present invention. As is apparent from FIG. 1, the image processing apparatus according to the present invention includes an image input unit 1, an input gradation correction unit 2, a color signal conversion unit 3, a color signal conversion unit 4, a black plate generation unit 5, a spatial filter unit. 6, an output gradation correction section 7, an image output section 8, and an image area separation section 9.

In the image processing apparatus having the above-described configuration, the image input section 1 is an image scanner or the like constituted by a photoelectric conversion element such as a CCD image pickup element, reads color image information of a document for each color, and outputs an electrical digital image signal. And output. The following description will be made on the assumption that the digital image signal read and converted by the image input unit 1 is an RGB color image signal having a resolution of 400 dpi and 8 bits for each color.

An image signal (R) output from the image input unit 1
(8 bits for each color of GB) is subjected to gradation correction by the input gradation correction unit 2. In the color signal conversion unit 3, the RGB image signal subjected to the gradation correction is converted into another color signal (for example, L ^* a
^* b ^* ). The L ^* a ^* b ^* image signal output from the color signal conversion unit 3 is supplied to a color signal conversion unit 4, where it is converted into another color signal (for example, YMC). A black plate is generated from the signal and converted into a YMCK image signal.

An image area determination result from an image area separation unit 9 described later is also input to the black plate generation unit 5, and the black plate generation coefficient is switched in accordance with the result. Y output from black plate generation unit 5
The MCK image signal is supplied to a spatial filter unit 6, where a spatial filtering process is performed for each color. Also,
An image area determination result from an image area separation unit 9 described later is also input to the spatial filter unit 6, and a spatial filtering process is performed on the image area determination result by, for example, switching a filtering coefficient.

YMC after spatial filtering
The K image signal is supplied to the output gradation correction unit 7, where the output gradation is corrected for each color so as to match the image output gradation characteristics. The output tone correction unit 7 also includes an image area separation unit 9 described later.
Are input, and the output gradation corresponding to the image area determination result is corrected.

The YMCK image signal whose output gradation has been corrected is supplied to an image output section 8. The image output unit 8 further includes:
The image area determination result from the image area separation unit 9 described later is also input,
In response to the image area determination result, for example, a screen is switched and an image is output.

Further, L ^* output from the color signal converter 3
Among the a ^* b ^* image signals, the L ^* signal is also supplied to the image area separation unit 9, and as described later, the image area of the character portion or the picture portion is determined for each pixel. This image area determination result is:
The black plate generation unit 5, the spatial filter unit 6, the output gradation correction unit 7, and the image output unit 8 supply the black plate generation unit 5, and as described above,
Processing corresponding to the image area determination result is performed.

[First Embodiment] Next, the image area separating section 9 will be described. FIG. 2 is a block diagram illustrating a configuration of the image area separation unit 9 according to the first embodiment of the present invention.

In FIG. 2, the image area separating section 9 according to the first embodiment has a shadow extracting section 11, a halftone dot extracting section 12, a line segment extracting section 13, a small area extracting section 14, and a line segment correcting section 15. It has a configuration. In addition, the small area extraction unit 14
It comprises a logical sum operation unit 16, a contraction processing unit 17, an expansion processing unit 18, and an inversion-logical product operation unit 19.

In the image area separating section 9 according to the first embodiment having the above-described configuration, the shadow extracting section 11 extracts, from the input image signal, a region having a high density, for example, a character or line segment such as black, blue or red. Alternatively, a relatively dense area such as hair, red flowers, green leaves, etc. is extracted even in the picture. At this time, a 1-bit image signal for each pixel is output from the shadow extraction unit 11 with the extracted pixels at a high level (logic “1”) and the unextracted pixels at a low level (logic “0”). The details of the shadow extraction unit 11 will be described later. The image signal output from the shadow extraction unit 11 is input to the small area extraction unit 14.

In the halftone dot extracting section 12, a halftone dot region included in the image is extracted from the input image signal. At this time, the halftone dot extraction unit 12 outputs a 1-bit image signal for each pixel in which the extracted pixels are set to the high level and the unextracted pixels are set to the low level. This dot extraction unit 12
Are output to the small area extracting unit 14.

As the halftone dot extracting section 12, the one described in the image processing apparatus proposed by the present inventor (see Japanese Patent Application Laid-Open No. 11-73503) can be used. Although the details are not described here, the outline is that the input image data is binarized, and the high-level pixels (or the low-level pixels) of the binary image data are obtained.
Is N1 × N1 (for example, N1 =
13) After determining whether or not a periodic structure is formed in the wide area, the halftone dot area is determined using the wide area of N2 × N2 (for example, N2 = 25). It is to extract.

The line segment extracting section 13 extracts characters and line segments contained in the image from the input image signal. At this time, the line segment extraction unit 13 outputs a 1-bit image signal of each pixel in which the extracted pixels are set to the high level and the unextracted pixels are set to the low level. This line segment extraction unit 13
Will be described later in detail. The image signal output from the line segment extraction unit 13 is input to the line segment correction unit 15.

In the small area extraction unit 14, the logical sum operation unit 16 receives the image data output from the shadow extraction unit 11 and the image data output from the halftone dot extraction unit 12 as two inputs, and performs logical operation on a pixel basis. Performs a sum operation. As a result of the OR operation, regarding the characters and the line segments, the shadow extracting unit 1
A signal equivalent to the result extracted in 1 is output from the logical sum operation unit 16.

On the other hand, for the picture area, most of the area is extracted by the dot extraction unit 12. However, in the area of very high density such as hair, the periodic structure of the halftone dots is lost. The part 12 cannot extract it. However, such a region having a very high density can be extracted by the shadow extracting unit 11, and the logical sum operation unit 16 outputs the result of extracting the entire pattern region.

The image data output from the OR operation unit 16 is supplied to a contraction processing unit 17 and becomes one input of a two-input inversion-AND operation unit 19. The contraction processing unit 17 performs contraction processing in an M1 × M1 (for example, M1 = 21) pixel region centering on the target pixel. FIG.
An example of the configuration of the contraction processing unit 17 is shown in FIG.

In FIG. 3, the image data output from the logical sum operation unit 16 includes FIFOs 35-1 to 35-20 for delaying one line cycle, and F / Fs for delaying the data by one pixel cycle. (Flip-flops) 36-1-1 to 36-21-21 are divided into a pixel group including 21 × 21 pixels centered on the target pixel. And F / F36-1-1 to 36-
The output from 21-21 is input to the AND operation unit 37, and the AND operation (AND processing) is performed. That is,
In the contraction processing unit 17, 21 × 21 around the pixel of interest is used.
= 441 pixels are subjected to a logical product operation, and the calculation result is set as an output value for the target pixel.

The image data output from the contraction processing section 17 is input to the expansion processing section 18. In the expansion processing unit 18,
M2 × M2 centered on the target pixel (for example, M2 = 3
3) Perform expansion processing in the pixel area. FIG. 4 shows an example of the configuration of the expansion processing unit 18.

In FIG. 4, the image data output from the contraction processing unit 17 are FIFOs 38-1 to 38-32 for delaying one line cycle, and F / F 39-32 for delaying the data for one pixel cycle. 1-1-3
9-33-33, 33
It is divided into a pixel group consisting of × 33 pixels. Then, the outputs from the F / Fs 39-1-1 to 39-33-33 are input to the logical sum operation unit 40, and the logical sum operation (OR processing) is performed. That is, the expansion processing unit 18 performs a logical OR operation on all 33 × 33 = 1809 pixels centering on the target pixel, and sets the calculation result as an output value for the target pixel.

The image data output from the expansion processing unit 18 is synchronized with the image data output from the OR operation unit 16 and becomes the other input of the inversion-AND operation unit 19. The inversion-AND operation unit 19 performs bit inversion (NO for each pixel of the image data input from the expansion processing unit 18).
After the T process), the logical product of the image data input from the logical sum operation unit 16 and the corresponding pixel is performed.

By configuring the small area extracting section 14 as described above, in this example, an area where high-level pixels have a width of 20 pixels or less is extracted as a small area, and an area having a width of 21 pixels or more is extracted as a small area. No extraction is performed, and only an area composed of line segments such as characters and line drawings can be extracted.

The operation result of the inversion-logical product operation unit 19, that is, the output result from the small area extraction unit 14, is output to the line segment correction unit 15
Is input to In the line segment correction unit 15, the small area extraction unit 14
The correction process is performed on the image signal from which the character / line segment extraction has been performed, which has been input from the line segment extraction unit 13, using the image signal input from the device. Then, the correction result is output from the line segment correction unit 15 as an image area separation result. Details of the line segment correction unit 15 will be described later.

The output data from the line segment corrector 15 is used as an image area determination result in the image area separator 9 as a black plate generator 5, a spatial filter 6, an output tone corrector 7, and an image output unit. 8 is supplied. Then, in each of these processing units, as described above, a process corresponding to the image area determination result is performed by switching the image conversion process or the image correction process, or the image conversion coefficient or the image correction coefficient.

Next, details of the shadow extracting unit 11 will be described with reference to FIG. FIG. 5 shows the shadow extraction unit 11.
FIG. 3 is a block diagram showing an example of the configuration of FIG. In FIG.
The image data input to the shadow extraction unit 11 is 3 × 3
Pixel average value calculation unit 21 and 5 × 5 pixel average value calculation unit 22
Is input to The 3 × 3 pixel average value calculation unit 21 calculates an average value of 3 × 3 pixels centering on the target pixel. The result calculated by the 3 × 3 pixel average value calculation unit 21 is output to a comparison unit 25 described later, and the comparison unit 25 compares the result with an output result of a limiter 24 described later.

The 5 × 5 pixel average value calculator 22 calculates the average value of 5 × 5 pixels centering on the target pixel. The result calculated by the 5 × 5 pixel average value calculation unit 22 is sent to the addition / subtraction unit 23, and the addition / subtraction unit 23 performs addition / subtraction with a predetermined value VALUE which is arbitrarily set empirically and input separately. . The operation result of the addition / subtraction unit 23 is output to a limiter 24, in which the value is limited between an upper limit value UPPER and a lower limit value LOWER which are arbitrarily set empirically and input separately.

That is, when the operation result of the addition / subtraction unit 23 is larger than the upper limit UPPER,
Is smaller than the lower limit LOWER, the lower limit L
Otherwise, the operation result of the addition / subtraction unit 23 is output from the limiter 24 as it is. Limiter 24
Is input to the comparison unit 25, and is compared with the calculation result of the 3 × 3 pixel average value calculation unit 21 described above. When the calculation result of the 3 × 3 pixel average value calculation unit 21 is larger than the output from the limiter 24, a high-level signal is output. When the calculation result is small or equal, a low-level signal is output.

FIG. 6 is a block diagram showing another example of the configuration of the shadow extracting unit 11. In the figure, the same reference numerals are given to the processing parts that perform the same processing as in FIG. 6, the image data input to the shadow extraction unit 11 is input to a 3 × 3 pixel average value calculation unit 21, a 5 × 5 pixel average value calculation unit 22, and a selector 26. The 3 × 3 pixel average value calculation unit 21 calculates an average value of 3 × 3 pixels centering on the target pixel. This 3 × 3 pixel average value calculation unit 21
Is output to a comparison unit 25 described later, and the comparison unit 25 compares the calculation result with an output result of a limiter 24 described later. The calculation result of the 3 × 3 pixel average value calculation unit 21 is also input to the selector 26.

The 5 × 5 pixel average value calculator 22 calculates the average value of 5 × 5 pixels centering on the target pixel. The result calculated by the 5 × 5 pixel average value calculation unit 22 is sent to the addition / subtraction unit 23, which performs addition / subtraction with the output result of the addition / subtraction value calculation unit 27 described later.
The operation result of the addition / subtraction unit 23 is output to a limiter 24, where the upper limit value
The value is limited between ER and lower limit LOWER. 5x5
The calculation result of the pixel average value calculation unit 22 is also input to the selector 26.

In the selector 26, the output results (target pixel values) of the input 3 × 3 pixel average value calculation unit 21, 5 × 5 pixel average value calculation unit 22 and color signal conversion unit 3 (see FIG. 1)
Is selected by an external input signal (not shown), and the result is input to the addition / subtraction value calculation unit 27. In the addition / subtraction value calculation unit 27, 5
The value to be added or subtracted from the × 5 pixel average value calculation unit 22 is calculated from the output result from the selector 26.

That is, the output value is calculated by adding, subtracting, multiplying and dividing a plurality of predetermined values with respect to the input value. Also,
The addition / subtraction value calculation unit 27 can be configured by an LUT (Look Up Table). In this case, the output value can be set relatively freely (stored in the LUT) according to the input value. The addition / subtraction unit 23, the limiter 24, and the comparator 25 have been described above, and thus description thereof will be omitted.

As described above, in the shadow extraction unit 11, the output result of the 3 × 3 pixel average value calculation unit 21 and the limiter 24
By comparing the output results of (1) and (2), it is possible to extract pixels having a high density and not extract pixels having a low density.
Also, average the pixel values of a relatively narrow area around the pixel of interest,
Since the average value of pixel values in a wider area is compared with a value obtained by performing a predetermined operation, it is possible to extract an area in which the detailed structure of characters and line segments is preserved.

Next, the details of the line segment extraction unit 13 will be described. In FIG. 7 showing an example of the configuration, the image data input to the line segment extraction unit 13 includes the first reduction units 30-1 to 30-1.
The image data is input to the N-th reduction unit 30-N, and the image data is reduced. For example, in the first reduction unit 30-1, the image is reduced by half in both the vertical and horizontal directions. In the second reduction unit 30-2, the vertical and horizontal directions of the image are each 1 /
4 is performed. Similarly, the N-th reduction unit 30-N
In this example, the image is reduced by 1 / (2N) in both the vertical and horizontal directions. As the image reduction method in the first reduction unit 30-1 to the N-th reduction unit 30-N, known reduction methods such as a simple thinning method, a four-point interpolation method, a sixteen-point interpolation method, a projection method, and a median value adoption method are used. Method is good.

The first reduction section 30-1 to the N-th reduction section 30-N
The image data reduced by the line extraction unit 31-1
To the line extraction unit 31-N. In addition, the line segment extraction unit 1
The image data input to 3 is also input to the line extraction unit 31-0. In the line extraction units 31-0 to 31-N,
A line segment having a predetermined range of width is extracted from the input image data.

In the case of this example, the first reduction units 30-1 to N-th
The image data is reduced by 1/2,
Since the reduction is performed to 1/4, 1/6,..., 1 / (2N), the line extraction units 31-0 to 31-N extract a line segment having a width of one pixel and two pixels. Line extraction unit 31-0
Details of the line extracting unit 31-N will be described later.

On the other hand, the image data input to the line segment extraction unit 13 is also input to the edge extraction unit 32. The edge extraction unit 32 extracts edge pixels included in the image data, and outputs the edge extraction results to the first enlargement unit 33-1 to the N-th enlargement unit 33-N. The details of the edge sleeve portion 32 will be described later.

The image data output from the line extracting units 31-1 to 31-N are respectively stored in the first enlarging units 33-1 to N-th.
The image data output from the enlargement unit 33-N and output from the edge extraction unit 32 are also input to the first enlargement unit 33-1 to the N-th enlargement unit 33-N. In the first enlargement unit 33-1 to the N-th enlargement unit 33-N, based on the image data input from the edge extraction unit 32, the line extraction units 31-1 to 31-N
The image data input from N is enlarged.

The first enlargement unit 33-1 to the N-th enlargement unit 33-N
Are the reciprocals of the reduction ratios in the first reduction unit 30-1 to the N-th reduction unit 30-N, that is, in this example, the values of 2, 4, 6,. I do. The details of the first to third enlargement units 33-1 to 33-N will be described later.

The first expanding section 33-1 to the N-th expanding section 33-N
The image data of the output result from the above-described line extraction unit 31-0 is input to the logical sum operation unit 34, and the logical sum operation is performed for each pixel. The image data of the output result from the OR operation unit 34 is the output result of the line segment extraction unit 13.

Subsequently, the line extraction units 31-0 to 31
-N will be described. As described above, in this example, 1
Although the processing for extracting a pixel and a line segment having a width of two pixels is described, the processing is not limited to this size, and the processing for extracting another line width is not limited. In the description here, the line extraction unit 31
−0 to the line extraction unit 31-N are assumed to be the same processing,
Only the line extracting unit 31-0 will be described,
Line segments may be extracted as different processes from 1-0 to the line extraction unit 31-N. FIG. 8 is a block diagram illustrating an example of a configuration of the line extracting unit 31-0.

In FIG. 8, the image signal input to the line extraction unit 31-0 detects a horizontal line having a line width of one pixel.
Pixel horizontal line detecting section 41, 1-pixel vertical line detecting section 42 for detecting a vertical line having a line width of 1 pixel, 1-pixel left oblique line detecting section 43 for detecting an ascending diagonal line having a line width of 1 pixel, 1 pixel 1-pixel right diagonal line detection unit 44 for detecting a right-upward diagonal line having a line width of 2 pixels, 2-pixel horizontal line detection unit 45 for detecting a horizontal line having a line width of 2 pixels, and detecting a vertical line having a line width of 2 pixels Two-pixel vertical line detector 46, a two-pixel left diagonal line detector 47 that detects a diagonally rising diagonal line having a line width of two pixels, and a two-pixel right diagonal line detector that detects a diagonally rising line having a line width of two pixels 48.

One pixel horizontal line detector 41, one pixel vertical line detector 42, one pixel left oblique line detector 43, one pixel right oblique line detector 4
4, 2 pixel horizontal line detection unit 45, 2 pixel vertical line detection unit 46, 2
The details of the pixel left diagonal line detection unit 47 and the two pixel right diagonal line detection unit 48 will be described later. Detected results of horizontal, vertical, left-upward diagonal lines and right-upward diagonal lines and 1-pixel-wide horizontal, vertical, upward-leftward diagonal lines, and right-upward diagonal lines detected by the detection units 41 to 48, respectively. Is the logical sum operation unit 4
9 and a logical sum operation of the detection result is performed for each pixel. Then, the result of the logical sum operation performed by the logical sum operation unit 49 is output as the line extraction result by the line extraction unit 31-0.

Next, the one-pixel horizontal line detector 41 will be described with reference to FIGS. FIG. 9 is a diagram illustrating the types of lines detected by each line detecting unit having a width of one pixel. 1
The pixel horizontal line detection unit 41 detects a horizontal line having a width of one pixel as shown in FIG. 9B using a 3 × 3 pixel matrix. 1
In FIG. 10 showing an example of the configuration of the pixel horizontal line detection unit 41, the input image data is the first row average value calculation unit 5.
1, second row average value calculation section 52, third row average value calculation section 5
3. Second row minimum value calculation section 54, first row maximum value calculation section 5
5, and is input to the third row maximum value calculation unit 56, respectively.

The first row average value calculation section 51 calculates the average of the pixel values of the three pixels in the first row of the 3 × 3 pixel matrix, that is, FIG.
The average of the pixel values of A, B, and C shown in FIG. , The pixel value of each pixel as _{P A, P B, P C} , average _{AVE (P A, P B,} P C) expressed as. In the second row average value calculation unit 52, AVE (P _D , P _E , P _F )
AVE (P _G , P _H ,
P _I ).

In the second row minimum value calculating section 54, D, E, F
Is obtained. From now on, the minimum value of a plurality of pixels will be expressed as MIN (P _D , P _E , P _F ). The first row maximum value calculation unit 55 determines the maximum value of the pixel values of A, B, and C. In the future, the maximum value of a plurality of pixels will be MAX (P _A , P _B , P
_C ). Further, the third row maximum value calculation section 56 calculates MAX (P _G , P _H , P _I ).

The calculation result of the second row average value calculation unit 52 and the first
The calculation results of the row average value calculation unit 51 are both input to the subtraction unit 57-1, and the first row
A process of subtracting the calculation result of the row average value calculation unit 51 is performed. The calculation result of the second row average value calculation section 52 and the calculation result of the third row average value calculation section 53 are both input to the subtraction section 57-2, and the third row average value calculation section 52 calculates the third A process of subtracting the calculation result of the row average value calculation unit 53 is performed.

The operation result of the subtraction unit 57-1 is compared with the comparison unit 58.
-1 is input and compared with a predetermined threshold value TH1.
The high level is output from the comparison section 58-1 when the operation result of the subtraction section 57-1 is larger than the threshold value TH1, and the low level is output when the result is equal to or smaller than the threshold value TH1. Also,
The operation result in the subtraction unit 57-2 is input to the comparison unit 58-2, and is compared with a predetermined threshold value TH1, and the subtraction unit 57-2
The high level is output from the comparing unit 58-2 when the result of the calculation at 2 is larger than the threshold value TH1, and the low level is output when the result is equal to or smaller than the threshold value TH1.

The operation result of the second row minimum value calculation section 54 is input to the comparison section 58-3, and is compared with a predetermined threshold value TH2. Is larger than the threshold value TH2, the high level is output from the comparison unit 58-3 when the value is equal to or smaller than the threshold value TH2.

The calculation result of the first row maximum value calculation unit 55 is input to the comparison unit 58-4, and is compared with a predetermined threshold value TH3. Is smaller than the threshold value TH3, the high level is output from the comparing section 58-4 if the level is larger or equal. The calculation result in the third row maximum value calculation unit 56 is input to the comparison unit 58-5 and compared with a predetermined threshold value TH3, and the calculation result in the third row maximum value extraction unit 56 is The high level is output from the comparing section 58-5 when the level is smaller than the threshold value TH3, and the low level is output when the level is higher or equal to the threshold value TH3.

All the comparison results of the comparison units 58-1 to 58-5 are input to the AND operation unit 59, and the AND operation unit 59
Then, the logical product of the comparison results of the comparison units 58-1 to 58-5 is calculated. The result output from the AND operation unit 59 is the output result of the one-pixel horizontal line detection unit 41. When the result is high, it is determined that there is a one-pixel width horizontal line as shown in FIG. In the case of the level, it is determined that there is no horizontal line of one pixel width.

That is, when all of the following equations (1) to (5) are satisfied, the one-pixel horizontal line detection unit 41 determines whether or not FIG.
It is determined that there is a horizontal line having a width of one pixel as shown in FIG. 9B, and a high level is output as a pixel value corresponding to D, E, and F in FIG. 9A. If at least one of (5) is not satisfied, it is determined that there is no horizontal line of one pixel width as shown in FIG.

[0066] _{AVE (P D, P E,} P F) -AVE (P A, P B, P C)> TH1 ... (1) AVE (P D, P E, P F) -AVE (P G, P _H , P _I )> TH 1 (2) MIN (P _D , P _E , P _F )> TH 2 (3) MAX (P _A , P _B , P _C ) <TH 3 (4) MAX (P _G , P _H , P _I ) <TH3 (5)

Next, the one-pixel vertical line detector 42 will be described. The one-pixel vertical line detection unit 42 detects a one-pixel width vertical line as shown in FIG. 9C using a 3 × 3 pixel matrix. FIG. 11 shows a configuration example of the one-pixel vertical line detection unit 42. The configuration is different from the one-pixel horizontal line detection unit 41 in FIG. 10 in that a first row average value calculation unit 51, a second row average value calculation unit 52, a third row average value calculation unit 53, and a second row minimum value calculation unit Part 5
4. The first row maximum value calculation section 55 and the third row maximum value calculation section 56 include a first column average value calculation section 61, a second column average value calculation section 62, a third column average value calculation section 63, and a second column average value calculation section 63. Column minimum value calculation unit 6
4. Only the first column maximum value calculation section 65 and the third column maximum value calculation section 66 are replaced, and are basically the same.

Therefore, here, the description will be made using equations. In the one-pixel vertical line detection unit 42, the following equations (6) to
When all the expressions (10) are satisfied, it is determined that there is a vertical line having a width of one pixel as shown in FIG.
A high level is output as a pixel value corresponding to E · H, and conversely, if at least one of (Equation 6) to (Equation 10) does not hold, one pixel width as shown in FIG. It is determined that there is no vertical line, and a low level is output for each.

[0069] _{AVE (P B, P E,} P H) one _{AVE (P A, P D,} P G)> TH4 ... (6) AVE (P B, P E, P H) -AVE (P C, P _F , P _I )> TH 4 (7) MIN (P _B , P _E , P _H )> TH 5 (8) MAX (P _A , P _D , P _G ) <TH 6 (9) MAX (P _C , P _F , P _I ) <TH6 (10)

Next, the one-pixel left oblique line detecting section 43 will be described. The one-pixel left oblique line detection unit 43 detects an obliquely leftward oblique line having a one-pixel width as shown in FIG. 9D using a 3 × 3 pixel matrix. FIG. 12 shows a one-pixel vertical line detection unit 42.
An example of the configuration will be described. The configuration is different from the one-pixel horizontal line detection unit 41 in FIG. 10 in that a first row average value calculation unit 51, a second row average value calculation unit 52, a third row average value calculation unit 53, and a second row minimum value calculation unit The unit 54, the first row maximum value calculation unit 55, and the third row maximum value calculation unit 56 include a lower left three pixel average value calculator 71, an upper left
Lower right diagonal three-pixel average value calculator 72, upper right three-pixel average value calculator 73, upper left / lower right diagonal three-pixel minimum value calculator 74, lower left three-pixel maximum value calculator 75, and upper right three-pixel maximum value calculator Only the unit 76 has been replaced, and is basically the same.

Therefore, here, the description will be made using equations. In the one-pixel left-slanting-line detecting unit 43, the following equation (1)
When all of the expressions (1) to (15) hold, FIG.
It is determined that there is a one-pixel-wide diagonal line as shown in
A high level is output as a pixel value corresponding to A.E.I in FIG. 9A. Conversely, Expressions (11) to (15) satisfy 1
If none of them is satisfied, it is determined that there is no oblique line rising to the left of one pixel width as shown in FIG.

AVE (P _A , P _E , P _I ) −AVE (P _D , P _G , P _H )> TH 7 (11) AVE (P _A , P _E , P _I ) −AVE (P _B , P _{C, P F)> TH7 ...} (12) MIN (P A, P E, P I)> TH8 ... (13) MAX (P D, P G, P H) <TH9 ... (14) MAX (P B, P _C , P _F ) <TH9 (15)

Next, the one-pixel oblique line detector 44 will be described. The one-pixel right diagonal line detection unit 44 detects an upward diagonal line with a one-pixel width as shown in FIG. 9E using a 3 × 3 pixel matrix. FIG. 13 shows one pixel right oblique line detection unit 4.
4 shows a configuration example. The configuration is different from the one-pixel horizontal line detection unit 41 in FIG. 10 in that a first row average value calculation unit 51, a second row average value calculation unit 52, a third row average value calculation unit 53, and a second row minimum value calculation unit The unit 54, the first row maximum value calculation unit 55, and the third row maximum value calculation unit 56 include an upper left three pixel average value calculator 81, an upper right and lower left diagonal three pixel average value calculator 82, and a lower right three pixel average value. Only the calculation unit 83, the upper right / lower left diagonal three-pixel minimum value calculator 84, the upper left three-pixel maximum value calculator 85, and the lower right three-pixel maximum value calculator 86 are replaced. A detailed description is omitted.

Therefore, here, the description will be made using equations. The one-pixel oblique line detection unit 44 calculates the following equation (1)
When all of the expressions (6) to (20) hold, FIG.
It is determined that there is a one-pixel wide diagonal line as shown in
High levels are output as pixel values corresponding to C, E, and G in FIG. 9A, and conversely, Equations (16) to (20) are 1
If none of these conditions hold, it is determined that there is no upward slanting line of one pixel width as shown in FIG.

AVE (P _C , P _E , P _G ) −AVE (P _A , P _B , P _D )> TH10 (16) AVE (P _C , P _E , P _G ) −AVE (P _F , P _H , P _I )> TH 10 (17) MIN (P _C , P _E , P _G )> TH 11 (18) MAX (P _A , P _B , P _D ) <TH 12 (19) MAX (P _F , P _H , P _I ) <TH13 (20)

Next, regarding the two-pixel horizontal line detection unit 45,
This will be described with reference to FIGS. FIG. 14 is a diagram illustrating the types of lines detected by each line detection unit having a width of two pixels. The two-pixel horizontal line detection unit 45 detects a horizontal line having a width of two pixels as shown in FIG. 14B using a 4 × 4 pixel matrix. FIG. 15 showing an example of the configuration of the two-pixel horizontal line detection unit 45.
, The input image data is divided into a first row average value calculation section 91, a second and third row average value calculation section 92, a fourth row average value calculation section 93, a second and third row minimum value calculation section 94, It is input to the one-row maximum value calculation unit 95 and the fourth-row maximum value calculation unit 96, respectively.

The first row average value calculation unit 91 calculates the average of the pixel values of the four pixels in the first row of the 4 × 4 pixel matrix, that is, FIG.
The average AVE (P) of the pixel values of J, K, L and M shown in FIG.
_J, P _K, P _L, the P _M) seek. In the second / third row average value calculation unit 92, AVE (P _N , P _O , P _P , P _Q ,
P _R , P _S , P _T , P _U ) by the fourth row average value calculation unit 93
Then, AVE (P _V , P _W , P _X , P _Y ) is obtained.

In the second / third row minimum value calculating section 94, N,
Minimum value MIN of each pixel value of O, P, Q, R, S, T, U
(P _N , P _O , P _P , P _Q , P _R , P _S , P _T , P _U )
Ask for. In the first row maximum value calculation unit 95, J, K, L,
The maximum value MAX (P _J , P _K , P _L ,
P _M ). In the fourth row maximum value calculation unit 96,
MAX (P _V , P _W , P _X , P _Y ) is obtained.

The calculation result of the second and third row average value calculation section 92 and the calculation result of the first row average value calculation section 91 are both subtracted by the subtraction section 97-
1 and a process of subtracting the calculation result of the first row average value calculation unit 91 from the calculation result of the second and third row average value calculation unit 92 is performed. Both the calculation result of the second and third row average value calculation section 92 and the calculation result of the fourth row average value calculation section 93 are input to the subtraction section 97-2, and the calculation of the second and third row average value calculation section 92 is performed. A process of subtracting the calculation result of the fourth row average value calculation unit 93 from the result is performed.

The operation result of the subtraction section 97-1 is compared with the comparison section 98.
-1 is input and compared with a predetermined threshold value TH13. When the operation result of the subtraction unit 97-1 is larger than the threshold value TH13, the high level is set. Is output from the comparing section 98-1.
Also, the operation result of the subtraction unit 97-2 is input to the comparison unit 98-2 and compared with a predetermined threshold value TH13, and the operation result of the subtraction unit 97-2 is larger than the threshold value TH13. The high level is output from the comparator 98-2 when the level is equal or lower.

The calculation result of the second / third row minimum value calculating section 94 is input to the comparing section 98-3, and is compared with a predetermined threshold value TH14. When the operation result is larger than the threshold value TH14, the high level is output from the comparison unit 98-3 when the operation result is equal to or smaller than the threshold value TH14.

The calculation result in the first row maximum value calculation unit 95 is input to the comparison unit 98-4, and is compared with a predetermined threshold value TH15. Is smaller than the threshold value TH15, the high level is output from the comparing section 98-4 when the level is larger or equal. The calculation result in the fourth row maximum value calculation unit 96 is input to the comparison unit 98-5, and is input to the predetermined threshold TH15.
The high level is obtained when the operation result of the fourth row maximum value calculation unit 96 is smaller than the threshold value TH15, and the low level is obtained when the operation result is larger or equal to the threshold value. Is output.

All the comparison results of the comparison units 98-1 to 98-5 are input to the AND operation unit 99, and the AND operation unit 99
, The logical product of the comparison results of the comparison units 98-1 to 98-5 is calculated. The result output from the AND operation unit 99 is the output result of the two-pixel horizontal line detection unit 45. When the result is high, it is determined that there is a two-pixel width horizontal line as shown in FIG. In the case of the level, it is determined that there is no horizontal line having a width of two pixels.

That is, when all of the following equations (21) to (25) hold, the two-pixel horizontal line detector 45 determines that there is a two-pixel horizontal line as shown in FIG. A high level is output as a pixel value corresponding to N, O, P, Q, R, S, T, and U in FIG. 14A, and conversely, even one of the equations (21) to (25) holds. If not,
It is determined that there is no horizontal line having a width of two pixels as shown in FIG.

AVE (P _N , P _O , P _P , P _Q , P _R , P _S , P _T , P _U ) −AVE (P _J , P _K , P _L , P _M )> TH 13 (21) AVE (P _N , P _O , P _P , P _Q , P _R , P _S , P _T , P _U ) −AVE (P _V , P _W , P _X , P _Y )> TH 13 (22) MIN (P _{N, P O, P P,} P Q, P R, P S, P T, P U)> TH14 ... (23) MAX (P J, P K, P L, P M) <TH15 ... (24) MAX (P _V , P _W , P _X , P _Y ) <TH15 (25)

Next, the two-pixel vertical line detector 46 will be described. The two-pixel vertical line detection unit 46 detects a two-pixel width vertical line as shown in FIG. 14C using a 4 × 4 pixel matrix.

FIG. 16 shows an example of the configuration of the two-pixel vertical line detector 46. The configuration is different from the two-pixel horizontal line detection unit 45 in FIG. 15 in that a first row average value calculation unit 91, a second and third row average value calculation unit 92, a fourth row average value calculation unit 93, a second and third row average value calculation unit 93 are used. The row minimum value calculation unit 94, the first row maximum value calculation unit 95, and the fourth row maximum value calculation unit 96 include a first column average value calculation unit 101,
Column average value calculation section 102, fourth column average value calculation section 103, second and third column minimum value calculation section 104, first column maximum value calculation section 10
Only the fifth and fourth column maximum value calculation units 106 have been replaced, and are basically the same.

Therefore, here, the description will be made using equations. In the two-pixel vertical line detector 46, the following equation (26) is used.
When Expressions (30) hold, it is determined that there is a vertical line having a width of two pixels as shown in FIG.
A high level is output as a pixel value corresponding to K, L, O, P, S, T, W, and X in FIG.
When even one of the expressions (30) is not satisfied, FIG.
It is determined that there is no vertical line having a width of two pixels as shown in (c), and a low level is output for each.

AVE (P _K , P _L , P _O , P _P , P _S , P _T , P _W , P _X ) −AVE (P _J , P _N , P _R , P _V )> TH 16 (26) AVE (P _K , P _L , P _O , P _P , P _S , P _T , P _W , P _X ) −AVE (P _M , P _Q , P _U , P _Y )> TH 16 (27) MIN (P _K , P _L , P _O , P _P , P _S , P _T , P _W , P _X )> TH 17 (28) MAX (P _J , P _N , P _R , P _V ) <TH 18 (29) MAX (P _M , P _Q , P _U , P _Y ) <TH18 (30)

Next, the two-pixel left-slanting-line detector 47 will be described. The two-pixel left diagonal line detection unit 47 detects a two-pixel wide diagonally left diagonal line as shown in FIG. 14D using a 4 × 4 pixel matrix.

FIG. 17 shows a configuration example of the two-pixel left oblique line detection section 47. The configuration is the same as that of the two-pixel horizontal line detector 45 shown in FIG.
The first row average value calculation section 91, the second and third row average value calculation section 92, the fourth row average value calculation section 93, the second and third row minimum value calculation section 94, the first row maximum value calculation The unit 95 and the fourth row maximum value calculation unit 96 include a lower left three pixel average value calculator 111, an upper left / lower right lower 10 pixel average value calculator 112, an upper right three pixel average value calculator 113, an upper left / lower right tilt Only the direction 10 pixel minimum value calculation unit 114, the lower left 3 pixel maximum value calculation unit 115, and the upper right 3 pixel maximum value calculation unit 116 are replaced.
The details are omitted because they are basically the same.

Therefore, here, the description will be made using equations. In the two-pixel left oblique line detection unit 47, the following equation (3)
When all of 1) to (35) hold, FIG.
It is determined that there is a two-pixel-width oblique line ascending left as shown in FIG. 14D, and JKNOPTPST in FIG.
A high level is output as a pixel value corresponding to U, X, and Y, and conversely, if at least one of Expressions (31) to (35) does not hold, a two-pixel width as shown in FIG. It is determined that there is no oblique line rising to the left, and each outputs a low level.

AVE (P _J , P _K , P _N , P _O , P _P , P _S , P _T , P _U , P _X , P _Y ) −AVE (P _R , P _V , P _W )> TH 19 ... _{(31) AVE (P J,} P K, P N, P O, P P, P S, P T, P U, P X, P Y) -AVE (P L, P M, P Q)> TH19 ... _{(32) MIN (P J,} P K, P N, P O, P P, P S, P T, P U, P X, P Y)> TH20 ... (33) MAX (P R, P V, P _{W) <TH21 ... (34)} MAX (P L, P M, P Q) <TH21 ... (35)

Next, the two-pixel right oblique line detecting section 48 will be described. The two-pixel right diagonal line detection unit 48 detects a diagonally right diagonal line with a two-pixel width as shown in FIG. 14E using a 4 × 4 pixel matrix.

FIG. 18 shows an example of the configuration of the two-pixel oblique line detection unit 48. The configuration is the same as that of the two-pixel horizontal line detector 45 shown in FIG.
The first row average value calculation section 91, the second and third row average value calculation section 92, the fourth row average value calculation section 93, the second and third row minimum value calculation section 94, the first row maximum value calculation The unit 95 and the fourth row maximum value calculation unit 96 include an upper-left three-pixel average value calculator 121, an upper-right / lower-left lower direction 10-pixel average value calculator 122, a lower-right three-pixel average value calculator 123, and an upper-right / lower-left lower direction Only the 10 pixel minimum value calculation unit 124, the upper left 3 pixel maximum value calculation unit 125, and the lower right 3 pixel maximum value calculation unit 126 are replaced.
The details are omitted because they are basically the same.

Therefore, here, the description will be made using equations. The two-pixel oblique line detection unit 48 calculates the following equation (3)
When all of the expressions (6) to (40) hold, FIG.
It is determined that there is a two-pixel-width oblique line rising to the right as shown in (e), and L, M, O, P, Q, R, S, and
A high level is output as a pixel value corresponding to TVW, and conversely, if at least one of Expressions (36) to (40) does not hold, a two-pixel width as shown in FIG. It is determined that there is no oblique line rising to the right, and each outputs a low level.

AVE (P _L , P _M , P _O , P _P , P _Q , P _R , P _S , P _T , P _V , P _W )-AVE (P _J , P _K , P _N )> TH 22 ... (36) AVE (P _L , P _M , P _O , P _P , P _Q , P _R , P _S , P _T , P _V , P _W )-AVE (P _U , P _X , P _Y )> TH22 ... (37) MIN (P _L , P _M , P _O , P _P , P _Q , P _R , P _S , P _T , P _V , P _W )> TH23 (38) MAX (P _J , P _K , P _{N) <TH24 ... (39)} MAX (P U, P X, P Y) <TH24 ... (40)

Next, details of the edge extracting unit 32 will be described. FIG. 19 is a block diagram illustrating an example of the configuration of the edge extraction unit 32. 19, the image data input to the edge extraction unit 32 is input to the 3 × 3 filter operation unit 131 and the floating binarization unit 133. The image data input to the 3 × 3 filter operation unit 131 is subjected to a filtering process with a preset 3 × 3 filter coefficient, and the operation result is output to the comparison unit 132. It is desirable that the 3 × 3 filter coefficient emphasizes an edge portion. As an example, a filter coefficient as shown in FIG. 20 is given.

The operation result of the 3 × 3 filter operation unit 131 input to the comparison unit 132 is compared with a preset threshold TH30, and the operation result of the 3 × 3 filter operation unit 131 is compared with the threshold TH30. If it is larger, a high-level signal is output, and if it is equal or smaller, a low-level signal is output. The output signal from the comparison unit 132 is input to the AND operation unit 135.

On the other hand, the image data input to the floating binarizing section 133 is subjected to a floating binarizing process. Then, the processing result is input to the 5 × 5 exclusive OR operation unit 134. Details of the floating binarization unit 133 will be described later.

The image data input to the 5 × 5 exclusive OR operation unit 134 is subjected to an exclusive OR operation of 5 × 5 pixels centering on the pixel of interest. That is, 5 × 5 = 25
When all the pixels are high-level signals or low-level signals, a low-level signal is obtained as a calculation result, and when even one pixel is different, a high-level signal is obtained. The operation result of the 5 × 5 exclusive OR operation unit 134 is input to the AND operation unit 135. Then, in the AND operation unit 135, the output signal from the comparison unit 132 and the output signal from the 5 × 5 exclusive OR operation unit 134 are AND-operated for each pixel,
The calculation result is output as an output result of the edge extraction unit 32.

Details of the floating binarization unit 133 will be described with reference to FIG. The image data input to the floating binarization unit 133 is input to the comparison unit 139 and the 3 × 3 average value calculation unit 136. The 3 × 3 average value calculation unit 136 calculates the average value of the 3 × 3 pixel values centered on the target pixel, and outputs the result to the addition unit 137. Adder 1
The calculation result of the 3 × 3 average value input to 37 is added to a predetermined addition value Val, and the result is output to the limit processing unit 138.

The upper limit value and the lower limit value are set in advance in the limit processing section 138.
7 is limited to the range of the upper and lower limit values. That is, when the calculation result input from the adding unit 137 is larger than the upper limit value, the upper limit value is set. When the calculation result is smaller than the lower limit value, the lower limit value is set. Is output as the calculation result of the limit processing unit 138.

The calculation result output from the limit processing unit 138 is input to a comparison unit 139, while the comparison operation with the image data input to the comparison unit 139, that is, the image data input to the floating binarization unit 133, is performed. Done. The image data input to the floating binarization unit 133 is output to the limit processing unit 138.
A high-level signal is output when the value is larger than the result of the calculation, and a low-level signal is output when the value is equal to or smaller than the calculation result. The output signal from the comparison unit 132 is input to the 5 × 5 exclusive OR operation unit 134.

As the processing in the edge extracting section 32, a known technique other than the above-described processing may be used, but it is preferable to extract a contour such as a line segment as faithfully as possible.

Next, details of the first to N-th enlargement units 33-1 to 33-N will be described with reference to FIGS. It should be noted that the first enlargement unit 33-1 to the N-th enlargement unit 33
Since -N performs almost the same processing, the first enlargement unit 33-1 will be described here as an example. FIG. 21 shows the first
FIG. 2 is a diagram for explaining processing contents in an enlargement unit 33-1;
FIG. 2 is a view for explaining enlargement condition determination in the first enlargement unit 33-1.

The first magnifying unit 33-1 receives the image data from which the line has been extracted by the line extracting unit 31-1 and the image data from which the edge has been extracted by the edge extracting unit 32. The image data output from the line extracting unit 31-1 is:
Since the original image data, that is, the image data input to the line segment extraction unit 12 has been reduced by １ ／ each in the vertical and horizontal directions, the input line extraction unit 3
In step 1-1, the image data subjected to the line extraction is enlarged twice vertically and horizontally.

However, if the enlargement processing is simply performed on the image data on which the line is extracted by the line extracting unit 31-1, the result will be a step-like rattling. This will be described with reference to FIG. 21. When an image as shown in FIG. 21E is input to the line segment extraction unit 13, the line extraction unit 31-1 obtains an extraction result as shown in FIG. Can be When this process is simply performed to enlarge the image twice vertically and horizontally, FIG.
Although the result is as shown in FIG. 1C, the result is that the step-like rattling is larger than that in FIG. 21E, and the line segment faithful to the input image is not obtained.

Therefore, the first enlargement unit 33-1 refers to the image data from which the edge has been extracted by the edge extraction unit 32, and refers to the image data from which the line has been extracted by the line extraction unit 31-1 Perform enlargement processing. At this time, the output from the first enlargement unit 33-1 is determined by the condition determination as described in FIG. For example, when a certain pixel of the image data input from the line extraction unit 31-1 is at a low level (LOW), the output from the first enlargement unit 33-1 is at a low level for all 2 × 2 pixels.

On the other hand, when a certain pixel of the image data input from the line extraction house 31-1 is at a high level (HIGH),
Condition determination is performed based on the values of the peripheral pixels of the pixel and the input value from the edge extraction unit 32, and the output from the first enlargement unit 33-1 is determined. By performing the enlargement processing of the image data subjected to the line extraction by the line extraction unit 31-1 according to the above condition determination, the input image data from the line extraction unit 31-1 as shown in FIG. , Based on the input image data from the edge extraction unit 32 as shown in FIG.
Image data subjected to the enlargement processing as shown in FIG. 21D is obtained.

Finally, the details of the line segment correction section 15 will be described. FIG. 23 is a block diagram illustrating an example of a configuration of the line segment correction unit 15. In FIG. 23, the output result of the small region extraction unit 14 and the output result of the line segment extraction unit 13 are input to the line segment correction unit 15. The output result of the small area extraction unit 14 is input to the expansion processing unit 141, where expansion processing of the input image data is performed. The processing result becomes one input of the two-input AND operation unit 142. The extraction result of the line segment extraction unit 13 is given to the AND operation unit 142 as the other input. Thereby, the logical product operation unit 14
In 2, the AND operation is performed for each pixel. Then, the calculation result is output as a line segment correction result.

By configuring the line segment corrector 15 as described above, there is no erroneous extraction in the picture area and a result faithful to the character / line image extracted by the line extractor 13 can be obtained. become. The correction result of the line segment correction unit 15 is output from the image area separation unit 9 as an image area separation result of the input image data.

As described above, according to the image area separating section 9 according to the first embodiment of the present invention, a character / line drawing / photograph / halftone dot and the like are mixed with a character / line image faithfully in the input image.
By extracting a line drawing and performing high-precision image area separation processing without erroneous extraction in a picture area, a good reproduced image can be obtained.

[Second Embodiment] Next, another embodiment of the image area separating section 9 will be described. FIG. 24 shows a second embodiment of the present invention.
FIG. 3 is a block diagram illustrating a configuration of an image area separation unit 9 according to the embodiment.

In FIG. 24, the image area separating section 9 according to the present embodiment includes a shadow extracting section 151, a halftone dot extracting section 152,
The configuration includes a line segment extraction unit 153, a small region extraction unit 154, and a line segment correction unit 155. The small area extraction unit 154 includes a logical sum operation unit 156 and a labeling unit 15.
7, contraction processing section 158, label number detection storage section 159,
It comprises a detected label number area removing section 160, a label feature amount calculating section 161, an inclusion relation determining section 162, and a binarizing section 163.

In the image area separating section 9 according to the second embodiment having the above structure, the shadow extracting section 151 extracts a high density area from the input image signal. And
The shadow extraction unit 151 outputs a 1-bit image signal for each pixel in which the level of the extracted pixel is high (logic “1”) and the level of the unextracted pixel is low (logic “0”). The image signal output from the shadow extracting section 151 is input to the small area extracting section 154.

Further, the dot extracting section 152 extracts a dot area included in the image from the input image signal. Then, the halftone dot extraction unit 152 outputs a 1-bit image signal for each pixel in which the extracted pixels are at a high level and the unextracted pixels are at a low level. The image signal output from the dot extracting unit 152 is input to the small area extracting unit 154. Note that the specific configurations of the shadow extraction unit 151 and the halftone dot extraction unit 152 are the same as those of the shadow extraction unit 11 and the halftone dot extraction unit 12 in the first embodiment, and the detailed description thereof will be duplicated. Here, it is omitted.

The line segment extraction section 153 extracts characters and line segments contained in the image from the input image signal.
Then, the line segment extraction unit 153 outputs a 1-bit image signal for each pixel in which extracted pixels are set to a high level and non-extracted pixels are set to a low level. This line segment extraction unit 1
Details of 53 will be described later. The image signal output from the line segment extraction unit 153 is input to the line segment correction unit 155.

The small area extracting section 154 includes the image data output from the shadow extracting section 151 and the halftone dot extracting section 15.
2 is input. The small area extraction unit 154 removes a large area such as a picture area,
A process of extracting only a small area composed of line segments such as characters and line drawings is performed. The image data resulting from the extraction is supplied to the line segment correction unit 155. The details of the small area extracting unit 154 will be described later.

In the line segment correction section 155, the small area extraction section 15
4 using the image signal input from
The correction processing is performed on the image signal from which the character / line segment extraction has been performed. Then, the correction result is output as an image area separation result. The specific configuration of the line-segment correcting unit 155 is the same as that of the line-segment correcting unit 15 according to the first embodiment.

The output data of the line segment correction unit 155 is used as an image area determination result in the image area separation unit 9 as a black plate generation unit 5, a spatial filter unit 6, an output gradation correction unit 7, and an image output unit in FIG. 8 is supplied. Then, in each of these processing units, as described above, a process corresponding to the image area determination result is performed by switching the image conversion process or the image correction process, or the image conversion coefficient or the image correction coefficient.

Next, details of the small area extracting section 154 will be described with reference to FIG. In the small area extraction unit 154, the logical sum operation unit 156 includes the image data output from the shadow extraction unit 151 and the halftone extraction unit 15
The image data output from 2 is input to 2 inputs, and a logical OR operation is performed for each pixel. As a result of the OR operation, a signal equivalent to the result extracted by the shadow extraction unit 151 is output from the OR operation unit 16 for characters and line segments.

On the other hand, most of the picture area is extracted by the halftone dot extracting section 152, but in the area of very high density such as the hair, the periodic structure of halftone dots is lost. It cannot be extracted by the unit 152. However, since such a region having a very high density can be extracted by the shadow extracting unit 151, the result obtained by extracting the entire picture region is output from the logical sum operation unit 156.

The image data output from the OR operation unit 156 is input to a labeling unit 157. The labeling unit 157 labels an input image in units of regions to which high-level signals are connected. The connection of the high-level signal may be four-neighbor connection in the up, down, left, or right direction, or eight-neighbor connection in the up-down, left, right, and diagonal directions. Is more desirable. The image signal labeled by the labeling unit 157 in units of connected areas of the high-level signal is input to the contraction processing unit 158, the detected label number area removing unit 160, and the label feature amount calculating unit 161.

The contraction processing section 158 performs contraction processing on the input labeled pixel signal in an M3 × M3 (for example, M3 = 21) pixel area centering on the target pixel. In the contraction processing here, all the label numbers assigned to the pixels in the M3 × M3 area centered on the target pixel are:
Only when it is equal to the label number assigned to the target pixel, the same number as the label number is set as the output value for the target pixel.

On the other hand, when the label number is not assigned to the pixel of interest, or when M3 × M3
If at least one of the pixels in the region does not have a label number or a pixel with a label number different from the target pixel, a signal corresponding to the absence of the label number is output. The image signal subjected to the contraction processing in the contraction processing unit 158 is output to the label number detection storage unit 159. The label number detection storage unit 159 detects and stores all the label numbers existing in the input image data.

Image data output from the labeling unit 157 is input to the detection label number area removing unit 160. The detection label number area removing unit 160 checks the label number assigned to each pixel from the input image data, and stores the label number in the label number detection storage unit 15.
It is checked whether or not the label number is included in the label number stored in 9. If it is included, a signal corresponding to the absence of the label number is output. Conversely, if it is not included, the label number is set as the output value for the target pixel. The output of the detected label number area removing section 160 is supplied to a binarizing section 161.

In the label feature value calculating section 161, for each label added area to which a different label has been added by the labeling section 157, a process of calculating the feature value of the label added area is performed. In the present embodiment, at least one of the number of pixels, the position of the region, the size of the region, and the label pixel density is calculated as the feature amount. The calculation result is supplied to the inclusion relation determination unit 162. The inclusion relation determination unit 162 determines the inclusion relation between the respective label-added areas to which different labels have been added by the labeling unit 157. The determination result is output to the detected label number area removing unit 160.
Supplied to

In addition to the processing described above, the detected label number area removing section 160 determines whether the label added area to which the label number stored in the label number detection storage section 159 has a predetermined characteristic amount has an inclusive relation. The region included in the label addition region is also removed based on the determination result of the determination unit 162.

The binarizing section 163 binarizes the image data input from the detected label number area removing section 160.
That is, a high-level signal is output when a label number is assigned to each pixel of the input image data, and a low-level signal is output when a label number is not assigned to each pixel.
The binarized output of the binarizing section 163 is supplied to the line segment correcting section 155 as an output result of the small area extracting section 154.

By configuring the small area extracting section 154 as described above, in this example, the area where the ON pixels are 21 pixels or more in width and the area continuous with the area are not extracted. Only the region constituted by the line segment is extracted.

Next, details of the line segment extracting section 153 will be described. In FIG. 25 showing an example of the configuration, the image data input to the line segment extraction unit 153 is
The image data is input to the 0-1 to N-th reduction units 170-N, and the image data is reduced. For example, the first reduction unit 170-1
In this case, the image is reduced by half in both the vertical and horizontal directions. In the second reduction unit 170-2, the image is reduced by 1/4 in both the vertical and horizontal directions. Similarly, the N-th
In the reduction section 170-N, 1 /
(2N) reduction is performed. The image reduction method in the first reduction unit 170-1 to the N-th reduction unit 170-N includes a simple thinning method, a four-point interpolation method, a sixteen-point interpolation method, a projection method,
A known reduction method such as a median value method may be used.

First reduction section 170-1 to N-th reduction section 170
Each of the image data reduced by -N
1-1 is input to the line extraction unit 171-N. The image data input to the line segment extraction unit 153 is
It is also input to 1-0. In the line extracting units 171-0 to 171-N, line segments having a predetermined range of width are extracted from the input image data.

In the case of this example, the image data is divided by the first reduction section 170-1 to the N-th reduction section 170-N into 1 /
Since the reduction is performed to 2, 1/4, 1/6,..., 1 / (2N), the line extraction units 171-0 to 171-N extract line segments having a width of one pixel and two pixels. I do. Details of the line extracting units 171-0 to 171-N will be described later.

On the other hand, the image data input to the line segment extraction unit 153 is also input to the edge extraction unit 172. The edge extraction unit 172 extracts an edge pixel included in the image data, and the edge extraction result is output to the first enlargement units 173-1 to 173-1.
The signal is output to the N-th expansion unit 173-N. Edge sleeve projection 17
The specific configuration of No. 2 is the same as that of the edge sleeve portion 32 in the first embodiment, and the details thereof will not be described here because they overlap.

The line extracting units 171-1 to 171-N
Output from the first enlargement unit 173-1
The image data input to the Nth enlargement unit 173 -N and output from the edge extraction unit 172 are also input to the first enlargement unit 173 -N.
1 to the N-th enlargement unit 173-N. 1st enlarged part 1
73-1 to the N-th enlargement unit 173-N, the edge extraction unit 1
72 based on the image data input from the
1-1: Enlarging processing of image data input from the line extracting unit 171-N is performed.

The first expanding section 173-1 to the N-th expanding section 173
The enlargement ratio at −N is the reciprocal of the reduction ratio at each of the first reduction unit 170-1 to the Nth reduction unit 170-N, that is, in this example, in both the vertical and horizontal directions, 2, 4, 6,. Value. Note that the specific configuration of the first enlarged section 173-1 to the N-th enlarged section 173-N is the same as the first enlarged section 33-1 to the N-th enlarged section 33-N in the first embodiment. The detailed description is omitted here because it is duplicated.

The first expanding section 173-1 to the N-th expanding section 173
−N and the image data of the output result from the line extraction unit 171-0 are input to the logical sum operation unit 174, and the logical sum operation is performed for each pixel. The image data of the output result from the logical sum operation unit 174 is the output result of the line segment extraction unit 153.

Subsequently, the line extracting unit 171-0 to the line extracting unit 1
71-N will be described. As described above, in the present embodiment, a process for extracting a line segment having a width of one pixel and two pixels is described. However, the present invention is not limited to this size, and may be a process for extracting a line width of another size. Further, in the description here, it is assumed that all the line extraction units 171-0 to 171-N perform the same processing, and only the line extraction unit 171-0 will be described. Part 171-
Lines may be extracted by using N as different processes. FIG. 26 is a block diagram illustrating another example of the configuration of the line extracting unit 171-0.

In FIG. 26, the image signal input to the line extraction unit 171-0 includes a one-pixel horizontal line left detection unit 181 and a one-pixel horizontal line right detection unit 18 for detecting a horizontal line having a line width of one pixel.
2, a one-pixel vertical line above detector 183 for detecting a vertical line having a line width of one pixel and a one-pixel vertical line lower detector 184 for detecting a left-upward diagonal line having a line width of one pixel; Detecting unit 185 and 1-pixel left oblique line lower detecting unit 186, 1-pixel right oblique line upper detecting unit 1 for detecting a right-upward oblique line having a line width of 1 pixel
87 and 1 pixel right diagonal under line detection unit 188 Detects a horizontal line having a line width of 2 pixels 2 pixel horizontal line left detection unit 189 and 2 pixel horizontal line right detection unit 190 detects a vertical line having a line width of 2 pixels Two pixel vertical line above detector 191 and two pixel vertical line below detector 19
A two-pixel left oblique line upper detecting unit 193 and a two-pixel left oblique line lower detecting unit 19 for detecting an ascending diagonal line having a line width of 2, 2 pixels
4, a two-pixel right diagonal line upper detecting unit 195 and a two-pixel right diagonal lower line detecting unit 196 for detecting an upward diagonal line having a line width of two pixels
Respectively.

One pixel horizontal line left detector 181, one pixel horizontal line right detector 182, one pixel vertical line upper detector 183, one pixel vertical line lower detector 184, one pixel left diagonal upper detector 185, one pixel left diagonal lower A detection unit 186, a detection unit 187 on the right diagonal line of one pixel,
One pixel right diagonal line under detection unit 188, two pixel horizontal line left detection unit 18
9, two-pixel horizontal line right detector 190, two-pixel vertical line detector 1
91, a two-pixel vertical line under detection unit 192, a two-pixel left diagonal under-detection unit 193, a two-pixel left diagonal under-detection unit 194, a two-pixel right diagonal under-detection unit 195, and a two-pixel right diagonal under-detection unit 196 It will be described later.

The horizontal / vertical / left-up diagonal lines, right-up diagonal lines, and 2-pixel-wide horizontal / vertical / left-up diagonal lines and right-up diagonal lines detected by the detection units 181 to 196, respectively. Is detected by the OR operation unit 197
And a logical sum operation of the detection result is performed for each pixel. Then, the result of the logical sum operation performed by the logical sum operation unit 197 is output as a line extraction result by the line extraction unit 171-0.

Next, the one-pixel horizontal line left detector 181 will be described with reference to FIG. One pixel horizontal line left detector 181
Detects a horizontal line having a width of one pixel as shown in FIG. 9F using a 3 × 3 pixel matrix. Now, 3 × 3 pixels are shown in FIG.
As shown in (a), they are called _{A to I,} and respective pixel values are P _{A to} P _I. At this time, when all of the following equations (41) to (45) hold, the one-pixel horizontal line left detecting unit 181 determines that there is a horizontal line of one pixel width as shown in FIG. 9 (a), a high level is output as a pixel value corresponding to D · E.
If even one of the expressions (45) does not hold, it is determined that there is no horizontal line having a width of one pixel as shown in FIG.

[0144] _{AVE (P D, P E)} -AVE (P A, P B)> TH41 ... (41) AVE (P D, P E) -AVE (P G, P H)> TH41 ... (42) MIN _{(P D, P E)>} TH42 ... (43) MAX (P A, P B) <TH43 ... (44) MAX (P G, P H) <TH43 ... (45) Note that, where, AVE (), MIN (), MAX
() Indicates the average value, the minimum value, and the maximum value of the pixel values in (), respectively. In addition, TH41 to TH44 are respectively predetermined thresholds.

By performing the above-described processing in the one-pixel horizontal line left detector 181, the horizontal line as shown in FIG. 9B can be detected, and the right end of the horizontal line can be detected. Becomes

Next, the one-pixel horizontal line right detector 182 will be described with reference to FIG. One pixel horizontal line right detector 182
Detects a horizontal line of one pixel width as shown in FIG. 9 (j) using a 3 × 3 pixel matrix. When all of the following equations (46) to (50) hold, the one-pixel horizontal line right detection unit 182 determines that there is a horizontal line of one pixel width as shown in FIG. 9A, a high level is output as a pixel value corresponding to E · F. Conversely, if even one of the equations (46) to (50) does not hold, one pixel as shown in FIG. It is determined that there is no horizontal line of the width, and a low level is output for each.

AVE (P _E , P _F ) -AVE (P _B , P _C )> TH44 ... (46) AVE (P _E , P _F ) -AVE (P _H , P _I )> TH44 ... (47) MIN (P _E , P _F )> TH 45 (48) MAX (P _B , P _C ) <TH 46 (49) MAX (P _H , P _I ) <TH 46 (50)

Next, the one-pixel vertical line detection unit 183 will be described with reference to FIG. One pixel vertical line detection unit 183
Detects a vertical line of one pixel width as shown in FIG. 9 (g) using a 3 × 3 pixel matrix. 1 pixel vertical line detector 18
In 3, when all of the following equations (51) to (55) hold, it is determined that there is a vertical line having a width of one pixel as shown in FIG. 9 (g), and B · E in FIG. Are output as the pixel values corresponding to the above, and conversely, the equations (51) to (5)
If at least one of 5) is not satisfied, it is determined that there is no vertical line having a width of one pixel as shown in FIG.

AVE (P _B , P _E ) −AVE (P _A , P _D )> TH47 (51) AVE (P _B , P _E ) −AVE (P _C , P _F )> TH47 (52) MIN _{(P B, P E)>} TH48 ... (53) MAX (P A, P D) <TH49 ... (54) MAX (P C, P F) <TH49 ... (55)

Next, the one-pixel vertical-line detection unit 184 will be described with reference to FIG. One pixel vertical line under detector 184
Detects a vertical line having a width of one pixel as shown in FIG. 9K using a 3 × 3 pixel matrix. 1 pixel vertical line detector 18
In 4, when all of the following equations (56) to (60) hold, it is determined that there is a vertical line having a width of one pixel as shown in FIG. 9 (k), and E · H in FIG. Are output as pixel values corresponding to the above, and conversely, equations (56) to (6)
If even one of 0) does not hold, it is determined that there is no vertical line of one pixel width as shown in FIG. 9 (k), and a low level is output for each.

AVE (P _E , P _H ) −AVE (P _D , P _G )> TH50 (56) AVE (P _E , P _H ) −AVE (P _F , P _I )> TH50 (57) MIN (P _E , P _H )> TH 51 (58) MAX (P _D , P _G ) <TH 52 (59) MAX (P _F , P _I ) <TH 52 (60)

Next, the one-pixel left oblique line detection unit 185 will be described with reference to FIG. 1 pixel left oblique line detection unit 18
5 detects a left-upward diagonal line having a width of one pixel as shown in FIG. 9H using a 3 × 3 pixel matrix. The one-pixel left-slanting on-line detection unit 185 calculates the following equations (61) to (6).
When all of the conditions 5) are satisfied, it is determined that there is a left-up diagonal line having a width of one pixel as shown in FIG. 9H, and the high level is set as a pixel value corresponding to A and E in FIG. On the contrary, when even one of the expressions (61) to (65) does not hold, it is determined that there is no one-pixel wide leftward oblique line as shown in FIG. I do.

AVE (P _A , P _E ) −AVE (P _D , P _G , P _H )> TH 53 (61) AVE (P _A , P _E ) −AVE (P _B , P _C , P _F )> TH53 ... (62) MIN (P A, P E)> TH54 ... (63) MAX (P D, P G, P H) <TH55 ... (64) MAX (P B, P C, P F) <TH55 ... (65)

Next, the one-pixel left oblique line under detection unit 186 will be described with reference to FIG. 1 pixel left oblique line under detection unit 18
6 uses a 3 × 3 pixel matrix to detect a left-upward diagonal line having a width of one pixel as shown in FIG. The one-pixel left-slanting under-detection unit 186 calculates the following equations (66) to (7).
When all of the conditions (0) are satisfied, it is determined that there is an obliquely upward diagonal line having a width of one pixel as shown in FIG. 9 (l), and a high level is set as a pixel value corresponding to E · I in FIG. 9 (a). On the contrary, if even one of the expressions (66) to (70) does not hold, it is determined that there is no left-up diagonal line having a width of one pixel as shown in FIG. I do.

AVE (P _E , P _I ) −AVE (P _D , P _G , P _H )> TH56 (66) AVE (P _E , P _I ) −AVE (P _B , P _C , P _F )> TH56 ... (67) MIN (P _E , P _I )> TH 57 ... (68) MAX (P _D , P _G , P _H ) <TH58 ... (69) MAX (P _B , P _C , P _F ) <TH58 ... (70)

Next, the one-pixel oblique line detection unit 187 will be described with reference to FIG. One pixel right oblique line detector 18
7 detects a right-upward oblique line having a width of one pixel as shown in FIG. 9 (i) using a 3 × 3 pixel matrix. The one-pixel oblique line detection unit 187 calculates the following equations (71) to (7).
When all of the conditions 5) are satisfied, it is determined that there is an oblique line rising to the right with a width of one pixel as shown in FIG. 9 (i), and a high level is set as a pixel value corresponding to CE in FIG. 9 (a). On the contrary, if even one of the equations (71) to (75) does not hold, it is determined that there is no oblique line rising to the right with one pixel width as shown in FIG. I do.

AVE (P _C , P _E ) −AVE (P _A , P _B , P _D )> TH59 (71) AVE (P _C , P _E ) −AVE (P _F , P _H , P _I )> TH59 ... (72) MIN (P C, P E)> TH60 ... (73) MAX (P A, P B, P D) <TH61 ... (74) MAX (P F, P H, P I) <TH61 ... (75)

Next, the one-pixel right oblique line lower detection section 188 will be described with reference to FIG. 1 pixel right oblique line under detection unit 18
Numeral 8 detects a right-upward oblique line having a width of one pixel as shown in FIG. 9 (m) using a 3 × 3 pixel matrix. The one pixel right oblique line under detection unit 188 calculates the following equations (76) to (8).
If all of the conditions (0) are satisfied, it is determined that there is an oblique line rising to the right with a width of one pixel as shown in FIG. 9 (m), and a high level is set as a pixel value corresponding to EG in FIG. 9 (a). On the contrary, if even one of the equations (76) to (80) does not hold, it is determined that there is no oblique line rising to the right with one pixel width as shown in FIG. I do.

AVE (P _E , P _G ) −AVE (P _A , P _B , P _D )> TH62 (76) AVE (P _E , P _G ) −AVE (P _F , P _H , P _I )> TH62 ... (77) MIN (P E, P G)> TH63 ... (78) MAX (P A, P B, P D) <TH64 ... (79) MAX (P F, P H, P I) <TH64 ... (80)

Next, the two-pixel horizontal line left detector 189 will be described with reference to FIG. 2-pixel horizontal line left detector 18
No. 9 detects a horizontal line having a width of two pixels as shown in FIG. 14F using a 4 × 4 pixel matrix. Now, 4 × 4 pixels are called _{J to Y} as shown in FIG. 14A, and their pixel values are set to P _{J to} P _Y. When all of the following equations (81) to (85) hold, the two-pixel horizontal line left detection unit 189 determines that there is a horizontal line having a two-pixel width as shown in FIG. a) N ・ O ・ P ・ R ・
A high level is output as a pixel value corresponding to S · T. Conversely, if even one of the equations (81) to (85) does not hold, a horizontal line having a width of two pixels as shown in FIG. Are determined to be absent, and each outputs a low level.

AVE (P _N , P _O , P _P , P _R , P _S , P _T ) −AVE (P _J , P _K , P _L )> TH65 (81) AVE (P _N , P _O , P _P , P _R , P _S , P _T ) −AVE (P _V , P _W , P _X )> TH65 (82) MIN (P _N , P _O , P _P , P _R , P _S , P _T )> TH66 ... (83) MAX (P J, P K, P L) <TH67 ... (84) MAX (P V, P W, P X) <TH67 ... (85)

Next, the two-pixel horizontal line right detector 190 will be described with reference to FIG. Two pixel horizontal line right detector 190
Detects a horizontal line having a width of two pixels as shown in FIG. 14 (j) using a 4 × 4 pixel matrix. When all of the following equations (86) to (90) hold, the two-pixel horizontal line right detection unit 190 determines that there is a horizontal line having a two-pixel width as shown in FIG. a) O, P, Q, S,
A high level is output as a pixel value corresponding to TU, and conversely, if at least one of Equations (86) to (90) does not hold, a horizontal line having a width of two pixels as shown in FIG. Is determined to be absent, and a low level is output for each.

[0163] _{AVE (P O, P P,} P R, P S, P T, P U) -AVE (P K, P L, P M)> TH68 ... (86) AVE (P O, P P, P _R , P _S , P _T , P _U ) −AVE (P _W , P _X , P _Y )> TH68 (87) MIN (P _O , P _P , P _R , P _S , P _T , P _U )> TH69 (88) MAX (P _K , P _L , P _M ) <TH 70 (89) MAX (P _W , P _X , P _Y ) <TH 70 (90)

Next, the two-pixel vertical line detector 191 will be described with reference to FIG. 2-pixel vertical line detection unit 191
Detects a vertical line having a width of two pixels as shown in FIG. 14 (g) using a 4 × 4 pixel matrix. When all of the following equations (91) to (95) hold, the two-pixel vertical line upper / lower portion 191 determines that there is a vertical line having a two-pixel width as shown in FIG. (A) KLOPS
A high level is output as a pixel value corresponding to T, and conversely, if at least one of Equations (91) to (95) does not hold, a vertical line having a width of two pixels as shown in FIG. Is determined to be absent, and a low level is output for each.

AVE (P _K , P _L , P _O , P _P , P _S , P _T ) −AVE (P _J , P _N , P _R )> TH 71 (91) AVE (P _K , P _L , P _O , P _P , P _S , P _T ) −AVE (P _M , P _Q , P _U )> TH 71 (92) MIN (P _K , P _L , P _O , P _P , P _S , P _T )> TH72 ... (93) MAX (P J, P N, P R) <TH73 ... (94) MAX (P M, P Q, P U) <TH73 ... (95)

Next, the two-pixel vertical line under detection unit 192 will be described with reference to FIG. 2-pixel vertical line under detector 192
Detects a vertical line having a width of two pixels as shown in FIG. 14K using a 4 × 4 pixel matrix. When all of the following equations (96) to (100) hold, the two-pixel vertical line under detection unit 192 determines that there is a two-pixel width vertical line as shown in FIG. 14 ・ a ・ O ・ P ・ S ・ T
A high level is output as a pixel value corresponding to W · X. Conversely, if at least one of Equations (96) to (100) does not hold, a vertical pixel having a width of two pixels as shown in FIG. It is determined that there are no lines, and each outputs a low level.

AVE (P _O , P _P , P _S , P _T , P _W , P _X ) −AVE (P _N , P _R , P _V )> TH74 (96) AVE (P _O , P _P , P _S , P _T , P _W , P _X ) −AVE (P _Q , P _U , P _Y )> TH74 (97) MIN (P _O , P _P , P _S , P _T , P _W , P _X )> TH75 ... (98) MAX (P N, P R, P V) <TH76 ... (99) MAX (P Q, P U, P Y) <TH76 ... (100)

Next, the two-pixel left oblique line detection section 193 will be described with reference to FIG. 2 pixels left diagonal horizontal side 1
Reference numeral 93 uses a 4 × 4 pixel matrix to detect a two-pixel-wide diagonally upward diagonal line as shown in FIG. This 2
When all of the following equations (101) to (105) hold, the pixel left oblique line detection unit 193 determines that there is an obliquely upward diagonal line having a width of two pixels as shown in FIG. a) outputs a high level as a pixel value corresponding to J, K, N, O, P, S, T, respectively.
1) When even one of the expressions (105) does not hold, FIG.
It is determined that there is no diagonal line rising to the left with a width of two pixels as shown in FIG.

[0169] _{AVE (P J, P K,} P N, P O, P P, P S, P T) -AVE (P R, P V, P W, P X)> TH77 ... (101) AVE (P _J , P _K , P _N , P _O , P _P , P _S , P _T ) −AVE (P _L , P _M , P _Q , P _U )> TH77 ... (102) MIN (P _J , P _K , P _N , P _O , P _P , P _S , P _T )> TH 78 (103) MAX (P _R , P _V , P _W , P _X ) <TH 79 (104) MAX (P _L , P _M , P _Q) , P _U ) <TH79 (105)

Next, the two-pixel left oblique line under detection unit 194 will be described with reference to FIG. 2-pixel left oblique line under detection unit 1
Reference numeral 94 uses a 4 × 4 pixel matrix to detect an obliquely upward diagonal line having a width of 2 pixels as shown in FIG. This 2
When all of the following equations (106) to (110) are satisfied, the pixel left oblique line under detection unit 194 determines that there is an obliquely upward diagonal line having a width of 2 pixels as shown in FIG. a) output high levels as pixel values corresponding to O, P, S, T, U, X, Y, respectively.
6)-When even one of the expressions (110) does not hold, FIG.
It is determined that there is no two-pixel-width diagonal line as shown in FIG. 4 (l), and outputs a low level.

[0171] _{AVE (P O, P P,} P S, P T, P U, P X, P Y) -AVE (P N, P R, P V, P W)> TH80 ... (106) AVE (P _O , P _P , P _S , P _T , P _U , P _X , P _Y ) −AVE (P _K , P _L , P _M , P _Q )> TH80 ... (107) MIN (P _O , P _P , P _S , P _T , P _U , P _X , P _Y )> TH 81 (108) MAX (P _N , P _R , P _V , P _W ) <TH 82 (109) MAX (P _K , P _L , P _M) , P _Q ) <TH82 (110)

Next, the two-pixel oblique line detection unit 195 will be described with reference to FIG. 2-pixel right oblique line detector 1
Reference numeral 95 denotes a diagonally right-upward diagonal line having a width of two pixels as shown in FIG. 14 (i) using a 4 × 4 pixel matrix. This 2
When all of the following expressions (111) to (115) are satisfied, the pixel right oblique line detection unit 195 determines that there is an upward diagonal line having a width of two pixels as shown in FIG. a) outputs a high level as a pixel value corresponding to L, M, O, P, Q, S, and T, and conversely, formula (11)
1) When even one of the expressions (115) does not hold, FIG.
4 (i), it is determined that there is no upward diagonal line with a width of two pixels, and outputs a low level, respectively.

AVE (P _L , P _M , P _O , P _P , P _Q , P _S , P _T ) −AVE (P _J , P _K , P _N , P _R )> TH83 ... (111) AVE (P _L , P _M , P _O , P _P , P _Q , P _S , P _T ) −AVE (P _W , P _U , P _X , P _Y )> TH83 (112) MIN (P _L , P _M , P _O , P _P , P _Q , P _S , P _T )> TH 84 (113) MAX (P _J , P _K , P _N , P _R ) <TH 85 (114) MAX (P _W , P _U , P _X) , P _Y ) <TH85 (115)

Finally, the two-pixel right oblique line under detection unit 196 will be described with reference to FIG. 2-pixel right oblique line under detection unit 1
Reference numeral 96 uses a 4 × 4 pixel matrix to detect a diagonally right-upward diagonal line having a width of two pixels as shown in FIG. This 2
When all of the following equations (116) to (120) hold, the pixel right diagonal underline detection unit 196 determines that there is a diagonally rightward diagonal line having a width of two pixels as shown in FIG. a) outputs a high level as a pixel value corresponding to O, P, R, S, T, V, W, and conversely, formula (11)
6) When any one of the expressions (120) does not hold, FIG.
It is determined that there is no upward slanting line having a width of two pixels as shown in FIG.

AVE (P _O , P _P , P _R , P _S , P _T , P _V , P _W ) −AVE (P _J , P _K , P _L , P _N )> TH86 (116) AVE (P _O , P _P , P _R , P _S , P _T , P _V , P _W ) −AVE (P _Q , P _U , P _X , P _Y )> TH86 (117) MIN (P _O , P _P , P _{R, P S, P T,} P V, P W)> TH87 ... (118) MAX (P J, P K, P L, P N) <TH88 ... (119) MAX (P Q, P U, P X , P _Y ) <TH88 (120)

As described above, according to the image area separating unit 9 according to the second embodiment of the present invention, erroneous extraction in a picture area is performed for an image in which characters, line drawings, photographs, halftone dots, and the like are mixed. Because there is no area, and areas that are not continuous are also extracted in a wide area, there is no longer a mixture of places to be extracted and places not to be extracted in one continuous area, and character / line drawings are faithfully extracted from the input image. By performing the high-precision image area separation processing, it is possible to obtain a good reproduced image.

In the image area separating unit 9 according to the second embodiment, a case has been described in which the small area extracting unit 154 has the label feature amount calculating unit 161 and the inclusion relation determining unit 162. The calculating unit 161 and the inclusion relation determining unit 162 can be omitted. In this case, the same effect can be obtained.

[0178]

As described above, according to the present invention,
When performing an appropriate reproduction process for each area on an image that contains characters, line drawings, photographs, halftone dots, etc., and outputting the image,
Since high-precision image area separation processing can be performed without extracting characters and line drawings faithfully from an input image and without erroneous extraction in a picture area, a high-quality image can be obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a basic configuration of an image processing apparatus according to the present invention.

FIG. 2 is a block diagram illustrating a configuration of an image area separation unit according to the first embodiment of the present invention.

FIG. 3 is a block diagram illustrating an example of a configuration of a contraction processing unit in the image area separation unit according to the first embodiment.

FIG. 4 is a block diagram illustrating an example of a configuration of an expansion processing unit in the image area separation unit according to the first embodiment.

FIG. 5 is a block diagram illustrating an example of a configuration of a shadow extraction unit in the image area separation unit according to the first embodiment.

FIG. 6 is a block diagram illustrating another example of the configuration of the shadow extraction unit in the image area separation unit according to the first embodiment.

FIG. 7 is a block diagram illustrating an example of a configuration of a line segment extraction unit in the image area separation unit according to the first embodiment.

FIG. 8 is a block diagram illustrating an example of a configuration of a line extraction unit in the image area separation unit according to the first embodiment.

FIG. 9 is a diagram illustrating types of lines detected by a line extraction unit having a width of one pixel.

FIG. 10 is a block diagram illustrating an example of a configuration of a one-pixel horizontal line detection unit.

FIG. 11 is a block diagram illustrating an example of a configuration of a one-pixel vertical line detection unit.

FIG. 12 is a block diagram illustrating an example of a configuration of a one-screen left-diagonal-line detecting unit.

FIG. 13 is a block diagram illustrating an example of a configuration of a one-screen right diagonal line detection unit.

FIG. 14 is a diagram illustrating types of lines detected by a line extraction unit having a width of two pixels.

FIG. 15 is a block diagram illustrating an example of a configuration of a two-pixel horizontal line detection unit.

FIG. 16 is a block diagram illustrating an example of a configuration of a two-pixel vertical line detection unit.

FIG. 17 is a block diagram illustrating an example of a configuration of a two-screen left diagonal line detection unit.

FIG. 18 is a block diagram illustrating an example of a configuration of a two-screen right diagonal line detection unit.

FIG. 19 is a block diagram illustrating an example of a configuration of an edge extraction unit.

FIG. 20 is a diagram illustrating an example of a filter coefficient.

FIG. 21 is a diagram for explaining processing in a first enlargement unit.

FIG. 22 is a diagram for explaining enlargement condition determination in a first enlargement unit.

FIG. 23 is a block diagram illustrating an example of a configuration of a line segment correction unit.

FIG. 24 is a block diagram illustrating a configuration of an image area separation unit according to a second embodiment of the present invention.

FIG. 25 is a block diagram illustrating an example of a configuration of a line segment extraction unit in an image area separation unit according to the second embodiment.

FIG. 26 is a block diagram illustrating an example of a configuration of a line extraction unit in an image area separation unit according to the second embodiment.

FIG. 27 is a block diagram illustrating an example of a configuration of an image area separation unit according to the related art.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Image input part, 2 ... Data storage part, 3 ... Operation processing part,
5: gradation correction section, 6: color signal conversion section, 8: image output section,
9: image area separation unit, 11, 151: shadow extraction unit, 1
2,152: halftone dot extraction unit, 13,153: line segment extraction unit,
14, 154: small area extraction unit, 15, 155: line segment correction unit, 17, 158: contraction processing unit, 18: dilation processing unit, 1
57: labeling unit, 159: label number detection storage unit,
160 ... detection label number area removing section, 161 ... binarization section

Continued on front page F-term (reference) 5C076 AA01 AA02 AA14 BA06 CA10 5C077 LL01 LL19 MP02 MP05 MP06 MP07 MP08 NN04 PP01 PP14 PP15 PP19 PP20 PP27 PP28 PP32 PP33 PP36 PP38 PP41 PP43 PP46 PP47 PP49 PP53 PP55 PP58 PP60 P61 PP68 P08 P08 RR19 5L096 AA07 BA17 BA18 FA03 FA19 FA42 FA43 FA44 FA54 FA78 GA12 GA21 GA23 GA34

Claims (8)

[Claims] An input unit for inputting image data; a shadow extracting unit for extracting a region having a high density from the image data input by the input unit; and a shadow extracting unit for inputting image data input by the input unit. Halftone dot extracting means for extracting a region composed of halftone dots, line segment extracting means for extracting a line segment having a width of a first predetermined number of pixels from the image data input by the input means, A small region extracting unit for extracting a region having a width of a second predetermined number of pixels from the region extracted by the shadow extracting unit and the region extracted by the halftone dot extracting unit; An image processing apparatus comprising: a line segment correction unit that corrects a line segment extracted by the line segment extraction unit based on the selected region. 2. The small area extracting means performs a logical OR operation on a pixel-by-pixel basis between the area extracted by the shadow extracting means and the area extracted by the halftone dot extracting means; A labeling unit that assigns a different label to each independent region with respect to the image data output from the OR operation unit, and for each label added region to which a different label is added by the labeling unit,
Label detecting means for determining whether or not the label-added area is an area having the width of the second predetermined number of pixels, and detecting the label added to the area by the label detecting means; 2. The image processing apparatus according to claim 1, further comprising an area removing unit configured to remove an independent area corresponding to the label based on the label. 3. The method according to claim 1, wherein the small area extracting means further calculates, for each label added area to which a different label has been added by the labeling means, a feature amount of the label added area; A label region inclusion relationship determining unit that determines an inclusion relationship between the label added regions to which different labels are added, wherein the region removing unit corresponds to the label based on the label detected by the label detecting unit. And, if the label added area has a predetermined feature amount, the area included in the label added area is removed based on the determination result of the label area inclusion relation determining means. The image processing device according to claim 2. 4. The width of the second predetermined number of pixels is set in conjunction with the width of the first predetermined number of pixels. The image processing device according to claim 3. 5. The feature amount calculated by the label feature amount calculating means includes a number of pixels, a position of an area, a size of the area,
4. The image processing apparatus according to claim 3, wherein the density is at least one of label pixel densities. 6. When performing image conversion processing or image correction processing on the input image data, image conversion processing, image correction processing, or image conversion based on image data output from the line segment correction means. 3. The image processing apparatus according to claim 1, wherein a coefficient or an image correction coefficient is switched. 7. A shadow extraction step for extracting a region having a high density from the input image data, a halftone dot extraction step for extracting an area composed of halftone dots from the input image data, A line segment extraction step of extracting a line segment having a width of a first predetermined number of pixels from the extracted image data; and a region extracted in the shadow extraction step and a region extracted in the halftone dot extraction step. Extracting a region having a width corresponding to a second predetermined number of pixels, based on the region extracted in the small region extraction step,
A line segment correction step of correcting the line segment extracted in the line segment extraction step. 8. When performing image conversion processing or image correction processing on input image data, image conversion processing or image correction processing is performed based on image data corrected and output in the line segment correction step. 8. The image processing method according to claim 7, wherein an image conversion coefficient or an image correction coefficient is switched.