JPH01195766A - Image processing device - Google Patents

Abstract

PURPOSE:To perform the binarization of picture information by satisfactory resolution and gradation property by deciding the classification of an image part based on information in which the maximum density difference in the local area of the picture information is normalized by a distance between image elements by which the maximum density difference is obtained, and selecting a threshold value to perform the binarization processing of the picture information according to a decided result. CONSTITUTION:An identification means 2 identifies and decides the classification of the image in the local area where a remarked image element is included by finding the distance between the maximum density within a prescribed range and the image element which takes the maximum density difference from the picture information outputted from a line buffer 1 synchronizing with a prescribed clock. A selection means 5 extracts a first threshold value supplied from a first threshold value generating means 5 or a second threshold value supplied from a second threshold value generating means 4 selectively setting the picture information as the threshold value to perform the binarization processing of the image information according to an identified and decided result. In such a way, it is possible to perform the binarization processing of a character part with superior resolution and that of a photographing part with superior gradation property.

Description

[Detailed Description of the Invention] [Objective of the Invention] (Industrial Field of Application) The present invention is capable of processing a document image in which a text portion and a photo portion are mixed, with high resolution of the text portion and high gradation of the photo portion. The present invention relates to an image processing device that can maintain and binarize images.

(Prior Art) In an image processing device (document image processing device) that can handle not only code information but also image information, high-contrast image parts such as characters and line drawings ( The text part) is binarized using a fixed threshold set in advance, and the image part (photo part) with gradation, such as a photograph, is binarized using a pseudo gradation method such as the dither method. There is.

Incidentally, there is a problem in that when a character part is binarized using the dither method, its resolution deteriorates, and when a photographic part is binarized using a fixed threshold value, its gradation is impaired. In order to avoid such problems, conventional methods separate image regions according to their image characteristics and binarize them by adaptively using the above-mentioned fixed threshold or threshold determined by the dither method for each region. It is supposed to be done.

However, in the conventional method, the maximum density difference ΔDIIlax of the image density in a local area of the read and input image information is detected,
This maximum density difference ΔD wax is compared with a predetermined threshold Th to determine whether the local area is a text area or a photograph area, and the form of the binarization process is switched.

However, in such a processing method, since the value of the maximum density difference ΔD 1llaX detected here is small for character parts with low contrast such as so-called faded characters,
It may be mistakenly determined to be a photographic section. As a result, a problem arose in that the resolution of text portions with low contrast was significantly impaired.

For example, as shown in FIG. 7, a document P that has been read and input has a text portion A with high contrast, a photograph portion B having two gradations,
In the case of a character portion C having a low contrast such as a faded character, a typical signal level of image information in each region A, B, and C of the document P is as shown in FIG. However, the dynamic range of image density is 8 bits [
For example, if it is given by 0 to FFIh, (4X
4) Maximum density difference ΔD ff1a in local area of pixel
x is [DD-PP] h in area A, [10-40] h in area B, and [10-40] in area C.
It will be about h. For this reason, the determination threshold Th is [80]
Using h, ΔD max > Th -...Text portion ΔD ff1aX≦Th...When determining the type of image of the local area as a photographic portion, not only the area B but also area C will be incorrectly determined as a photographic portion. This problem occurs. Further, when [30] h is used as the determination threshold Th, there is a problem that there is a possibility that the area B will be determined as a character portion.

In this way, conventional devices that identify the type of area by determining the maximum density difference ΔD max using a predetermined threshold value are capable of determining the resolution of text for document images that include text with low contrast. There are problems in that it is very difficult to binarize well and to binarize photographic areas with good gradation.

(Problem to be Solved by the Invention) In this way, conventional devices perform binary processing on image information in which text and photo areas coexist without simultaneously satisfying the resolution for the text area and the gradation for the photo area. On this occasion,
Especially when it contains characters with low contrast,
There have been problems such as that it is very difficult to adaptively control the form of the binarization process.

The present invention has been made in consideration of these circumstances, and its purpose is to provide high resolution for the text portion and high resolution for the photographic portion, even if the image information includes text portions with low contrast. An object of the present invention is to provide an image processing device that can perform binarization with good gradation.

[Configuration of the Invention (Means for Solving the Problems) The image processing device according to the present invention calculates the maximum density difference from image information within a predetermined range, and calculates the maximum density difference from the image information within the predetermined range. Find the distance between pixels that takes
The maximum density difference is normalized using this distance between pixels, and its value is determined. Then, the image information within the predetermined range is binarized by selectively using a threshold value determined from the image information within the predetermined range or a preset threshold value according to the determination result.

In other words, it is possible to identify the type of image by using not only the maximum density difference in local image parts, but also the characteristics of the density change, and to effectively apply binarization processing according to the type of image. It is characterized by the fact that

(Operation) According to the present invention, the maximum density difference of image information within a predetermined range defined as a local area is normalized by the distance between pixels that have the maximum density difference, and the type of image is determined by calculating the density gradient. Since this determination is made, even a low-contrast text portion with a small maximum density difference will not be erroneously identified as a photographic portion because its density gradient is steep. As a result, even if a document image contains various types of text and photo areas, it is possible to accurately identify the text and photo areas and adaptively set thresholds for binarization. Therefore, it is possible to perform binarization processing on text portions with good resolution and on photographic portions with good gradation.

(Embodiment) Hereinafter, one embodiment of the present invention will be briefly described with reference to the drawings.

FIG. 1 is a diagram showing the concept of image processing in an image processing apparatus according to an embodiment. This image processing device has an image-
Image information read and input using a reading device such as a scanner,
For example, each pixel is input as 8-bit digital data. The line buffer 1 temporarily stores such image information and uses it for the image processing described below.

The identification means 2 determines the maximum density difference within a predetermined range and the distance between pixels having the maximum density difference from the image information outputted from the line buffer 2 in synchronization with a predetermined clock, and identifies the pixel of interest. This is to identify and determine the type of image of the included local area. The selection means 5 is selectively switched according to the result of this discrimination judgment, and the first threshold value given from the first threshold value generation means 3 or the second threshold value given from the second threshold value generation means 4 is used to convert the image information into binary values. It is selectively extracted as a threshold value for processing. The image information read from the line buffer 1, delayed by a predetermined timing via the delay means 7, and guided to the comparison means 6 is binarized using the threshold value extracted via the selection means 5, and is output. be done.

FIG. 2 is a schematic configuration diagram of an embodiment device that executes the above-described processing, and FIG. 3 is a diagram showing a more detailed configuration of the identification means 2 in the embodiment device.

The identification means 2 that executes the image type identification process described above includes:
As shown in FIG. 2, the input stage includes a smoothing circuit 20 for smoothing the image information read out from the line buffer 1, and an edge emphasizing circuit 21 for emphasizing edge components of the smoothed image signal. There is.

These smoothing circuits 20. For example, when a pixel of interest is specified as a shaded area as shown in FIG. 4, the preprocessing by the edge enhancement circuit 21 is performed by
X4) In order to perform identification processing, which will be described later, using a pixel as a local area, the process is further performed on the (8×8) pixel area surrounding the local area. Through this processing, noise components of the image information are removed, and edge components are emphasized using Laplacian processing or the like.

The preprocessed image information is input to the maximum value/minimum value calculation circuit 22, and the maximum density value D max and minimum density value D akin in a predetermined local area consisting of the (4×4) pixels are detected. It will be done. The subtraction circuit 23 calculates the maximum density difference ΔD IIax from the maximum density value Dff1aX and the minimum density value Dmin as ΔD wax −D.
It is calculated as 5ax-D l1in. Further, the distance calculating circuit 24 calculates the distance between the pixels as L=, /i2+32 from the positional information 1+J of the pixel having the maximum density value DIlax and the pixel having the minimum density value Dm1n. The division circuit 25 uses the maximum density value ΔD wax obtained in this way and the distance between pixels as follows: F=Da+ax+L Then, the maximum density value D wax is normalized by the distance, and the density gradient F is obtained. . Information on this density gradient F is determined by a predetermined discrimination threshold Th in a comparator circuit 2B, and the type of image information of the local area is determined. This determination is as follows: F>Th...Pixel in character area F≦Th
...Performed as a pixel in a non-character area.

The first threshold value generating means 3 is, for example, a maximum value/minimum value calculation circuit that detects a maximum density value DmaX and a minimum density value Dmin of the density from the image information stored in the line buffer 1, respectively. 30. A dynamic threshold calculation means 31 that dynamically calculates a threshold Bh for binarizing image information according to the detection result, for example, as Bh - (Dmax + DIIlin) / 2, and this dynamic threshold calculation means 31 and means 32 for outputting the threshold value Bh determined in step 1 to the selection means 5.

Further, the second threshold value generating means 4 is composed of, for example, a memory storing dither pattern information (dither matrix),
The information is output to the selection means 5. This dither pattern information (dather matrix) is
For example, it is given as a matrix pattern of threshold values as shown in FIG.

Then, the threshold value Bh or the dither pattern is selectively extracted based on the above-described identification determination result, and the image information is subjected to binary processing.

The above-mentioned identification process, which is a characteristic part of this apparatus, will be explained in more detail with reference to FIGS. 3 and 5.

As mentioned above, smoothing processing and edge enhancement processing (8X
8) Since the processing is performed on a pixel area, an 8-line buffer is used as the line buffer l.

The image information stored in this 8-line buffer 1 is
As shown in the timing chart in the figure, the signals are input to the smoothing circuit 20 in time series as shown by the signal DIN according to the clock CLK of a predetermined period.

The smoothing here first focuses on the pixel of interest (aXa
) When referring to pixels and sorting their pixel densities,
This is done by setting the density located at the center as the density of the reference pixel. Specifically, at the first clock, from the pixel in the (J-3) column and (+-3) row shown in FIG.
3) Information on 8 pixels up to the pixels in column (1+4) row is input in parallel, and each of the three adjacent pixels is smoothed.

Then, at the second clock, (J-2) column (1-3)
Input information on 8 pixels from the pixel in the row to the pixel in the (J-3) column and (1+4) row, and at the third clock, (J
-1) Column (1-3) row pixel to (J-3) column (
++4) Manually input information for 8 pixels up to the pixels in the row.

Each time smoothing information for three pixels adjacent in the column direction is obtained, smoothing processing is again performed between them, thereby smoothing the image information two-dimensionally (two-dimensionally).

The image information smoothed in this manner is input to the edge emphasis circuit 21 at the timing SUN.

This edge enhancement circuit 21 performs edge enhancement processing using a Laplacian filter on pixel information in a (3×3) pixel area centered on a reference pixel with G (1, J
) -F (1, J) - 2F (1, C). G (1, J) is the edge-enhanced image signal output, and F (+, J) is the output of the input image signal,
2F(+, J) indicates the Laplacian which is the two-time differential of the input image F (1, J). This Laplacian is
For example, 2F (Iri -F (Ill, H1F (+-1, J
)+ F (1,++1)+ F (Ii-1)-4・
F (LJ).

However, in the fourth black cross, (J-2) column (1-2)
Since the smoothed image data from the row to the (++3)th row is input, edge enhancement processing is performed in the row direction. Then, as the clock advances, edge enhancement processing is performed sequentially in the column direction. By the above edge enhancement processing, the (J-1) column (
Edge-enhanced data EDG from line +-1) to line (++2) is output.

Therefore, the maximum value/minimum value detection circuit 22 calculates the maximum value and minimum value of each of the four pixels in the column direction, and calculates the maximum value and minimum value of each of the four pixels in the next column at the next clock. I'm looking for it. The maximum and minimum density values obtained in each of the four consecutive columns are then compared with each other to calculate the maximum and minimum density values within the (4×4) pixel area, respectively. At this time, the position of the pixel that obtained the maximum density value and the position of the pixel that obtained the minimum density value are determined at the same time.

The subtraction circuit 23 and the distance calculation circuit 24 calculate the maximum density difference from the maximum density value and the minimum density value obtained in this way, and also find the distance between the pixels from which the maximum density difference is obtained. It is output at the appropriate timing. With respect to this signal, the division circuit 25 outputs the normalized density difference information (density gradient) at a timing I)TR, which is used for determining the image type.

According to the present device configured in this way, even if the maximum density difference value is small and the character image has a low contrast, it is possible to effectively utilize the characteristic that the character image has a steep density change peculiar to the character image. Therefore, it is possible to reliably determine the low-contrast character image as a character part, and to set an appropriate threshold for binarizing the character part. Furthermore, the known information can be adaptively set according to the image information. As a result, even if a document image contains multiple types of information, text portions can be binarized with good resolution, and photographic portions can be binarized with good gradation.

Note that the present invention is not limited to the embodiments described above. For example, the apparatus may be configured to variably set the size of the local area depending on the image to be processed. In addition, the means for adaptively generating the threshold value can be modified in various ways.
The dither pattern used for value conversion is also not particularly limited. Further, the size of the dither matrix is not limited, and the dither pattern can be arranged not only in a dot-distributed manner but also in a dot-concentrated manner. Furthermore, in the embodiment, the density information was directly obtained from the read and input image information, but it is also possible to obtain the feature amount using a value converted from this amount to image density (logarithm of the reciprocal of the reflectance). . In addition, the present invention can be implemented with various modifications without departing from the gist thereof.

[Effects of the Invention] As explained above, according to the present invention, the maximum density difference in a local area of the image information is normalized by the distance between the pixels from which the maximum density difference is obtained, and the image part is determined based on the information. Since the type is determined and a threshold value for binarizing the image information is selected and set according to the determination result, text parts can be binarized with good resolution regardless of their contrast. For photographic areas, great practical effects can be achieved, such as the ability to binarize with good gradation. As a result, it is possible to obtain high-quality binarized images that serve as the basis for various types of image processing, and to improve the processing efficiency.

[Brief explanation of the drawing]

Figure 1 is a diagram showing the concept of image processing in the present invention, Figure 2 is a diagram showing the concept of image processing in the present invention.
The figure is a schematic diagram of the main parts of an image processing device according to an embodiment of the present invention, FIG. 3 is a diagram showing a detailed configuration example of the identification means in the embodiment device, and FIG. FIG. 5 is a diagram schematically showing the concept, FIG. 5 is a diagram showing processing operation timing of the embodiment apparatus, and FIG. 6 is a diagram showing an example of a dither pattern. FIG. 7 is a diagram showing an example of a document image to be processed, and FIG. 8 is a diagram showing the density level of a typical image signal of the image to be processed shown in FIG. l...Line buffer, 2...Identification means, 3...
First threshold generation means, 4...Second threshold generation means, 5
... Selection means, 6. Comparison means, 20. Smoothing circuit, 21. Edge emphasis circuit, 22. Maximum value.
Minimum value detection circuit, 23... Subtraction circuit, 24... Distance calculation circuit, 25... Division circuit, 2B... Comparison circuit,
30... Maximum value/minimum value detection circuit, 31... Dynamic threshold value calculation means. Applicant's agent Patent attorney Takehiko Suzue No. 4 l Fig. 5 Fig. 60 No. 70 107jSB Fig.

Claims (1)

[Claims] means for determining the maximum density difference from image information within a predetermined range; means for determining a distance between pixels that take the maximum density difference from image information within the predetermined range; and means for determining this normalized density difference and setting a threshold value for binarizing image information within the predetermined range according to the determination result. Image processing device.