JPH01243668A - Picture processing device - Google Patents

Abstract

PURPOSE:To binarizing process a character part by good resolution and a photograph part by good gradation respectively by discriminating the kind of a picture by using not only the maximum density difference of a local picture part but the feature of the density level of it and performing effectively binarizing processing respectively corresponding to the kind of the picture. CONSTITUTION:A discriminating part 2 obtains the maximum density difference within a prescribed range and mean density within the prescribed range as reference density from a picture information outputted from a line buffer 1, and discriminates the kind of the picture in which a notice picture element is included by a value that said maximum density difference is normalized by the mean density. A selecting means 5 is switched selectively according to this result, and a first threshold value from a first threshold value generating means (dynamic threshold value calculating means) 3 or a second threshold value from a second threshold value generating means 4 is extracted selectively as a threshold value for binarizing processing the picture information. Then, the picture information is introduced to a comparing means 6, and is binarizing processed by this threshold value. Thus, as for even the picture information in which the character part of low contrast is included, the character part and the photograph part can be binarized with satisfactory resolution and with satisfactory gradation respectively.

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 past, the maximum density difference ΔD of image density in a local area of the scanned and inputted image information is detected, and this maximum density difference ΔD is set between a predetermined threshold Th and 1a.
X is compared 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 detected here is small WaX for low-contrast character parts such as so-called faded characters, they are incorrectly identified as photographic parts. There is a thing. 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. 8, a document P that has been read and input has a character part A1 with high contrast, a photograph part B having gradation,
When the image information is composed of character portions C with low contrast such as faded characters, typical signal levels of image information in each area A, B, and C of the document P are as shown in FIG. Currently, the dynamic range of image density is 8 bits [0 to
FF] h, for example (4X4)
The maximum density difference ΔD in the local area of a pixel is the above type ■ ax [DD-PFI in area A, [10 to 40] in area B
h.

In region C, it is about [to-40]h. For this reason, [80] h is used as the determination threshold Th, and ΔD > Th ... character part, Wa
X ΔD ≦Th...When determining the type of image of the local area as photographic area aX, the area B
In addition, there arises a problem that up to area C is erroneously determined as a photographic area. Also, as the determination threshold Th, [30] h
When using this, there was a problem that there was a risk that area B would be determined as a character section.

In this way, conventional devices that identify the type of area by determining the maximum density difference ΔD using a predetermined threshold value Wa There are problems such as that it is very difficult to binarize well and to binarize photographic areas with good gradation.

(Problems to be Solved by the Invention) As described above, in the conventional device, it is difficult to perform binary processing on image information in which text and photographs are mixed while simultaneously satisfying the resolution for the text and the gradation for the photographs. ,
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.

[Structure of the Invention] (Means for Solving the Problems) An image processing device according to the present invention calculates the maximum density difference from image information within a predetermined range, and calculates the average of the image information within a region including the predetermined range. One of the density, maximum density, and minimum density is determined as a reference density for image information within the predetermined range, and the maximum density difference is normalized using this reference density to determine its value. Then, the image information within the predetermined range is binarized by selectively using a threshold dynamically determined from the image information within the predetermined range or a preset threshold according to the determination result. It is.

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

(Operation) According to the present invention, the maximum density difference of the image information within a predetermined range defined as a local area is normalized from the reference density in that area, and from that value it is possible to determine how the image information is determined. Since the type of image is determined by determining whether the image has such properties, image areas and text areas with a small maximum density difference are compared with images in photographic areas and text areas, such as whether the reference density is high or low. It is no longer necessary to determine the image type based on the characteristics specific to the type and perform erroneous binarization processing as in the past. As a result, even if a document image contains a mixture of various text and photo areas, the text and photo areas can be accurately identified and the thresholds for binarization can be adaptively set for each. Therefore, it is possible to perform binarization processing on text portions with good resolution and on photographic portions with good gradation.

(Example) Hereinafter, an example of the present invention will be 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. Image information read and input by a reading device such as an image scanner is input to this image processing device as, for example, 8-bit digital data per pixel.The line buffer l temporarily stores such image information. The image is then stored as an image and used for the image processing described below.

The identification means 2 calculates the maximum density difference within a predetermined range and the average density as a reference density within the predetermined range from the image information outputted from the line buffer 1 in synchronization with a predetermined clock, and The type of image of the local area including the pixel of interest is identified and determined based on the value obtained by normalizing the maximum density difference by the average density. 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 l, delayed and timing-adjusted via the delay means 7, is led to the comparison means 6, and selectively extracted by the comparison means 6 via the selection means 5. The data is binarized using a threshold value and output.

For example, when the pixel of interest is given by (t, j) as shown in FIG. Image information within a predetermined range (for example, 4x4-166 pixel area) including the pixel (L, j) is read out in parallel, and the maximum image density (D) within that range is calculated.
and the minimum inter-ax image density (D), respectively.

■in The subtracter 21 converts the difference sin ΔD −D −D wax saw gain between the maximum image density (D”) and the minimum image density ax (D) detected by the maximum value/minimum value detection circuit 20 into the predetermined value. It is calculated as the maximum concentration difference (ΔD)saw within the range.This maximum concentration difference (ΔD)Ia
X is given to the division circuit 22, and the average value calculation circuit 23 divides it by the average image density D within the predetermined range obtained as described later, and calculates the normalized maximum density difference (ΔD
) is calculated as axn ΔD −ΔD +D laXn IaX a. Note that although the average density D is used here as the reference density for normalizing the maximum density difference ΔDllax, the maximum image density value D and the minimum image density value D within the above-mentioned predetermined range are used as the reference wax.
It is also possible to adopt it as a sin concentration. In addition, surrounding pixels including the reference density within the above-mentioned predetermined range are set as the processing target area, for example, (8X8-888 pixel area or (8X8-84 pixel area)
It is also possible to obtain it from image information of the pixel area).

The normalized maximum concentration difference (ΔD
) is determined by the comparison circuit 26 using a predetermined discrimination threshold value ThaXn to determine the type of image information of the local area. This determination is as follows: ΔD > Th... Pixel of character area - a'
xn ΔD ≦Th ... Pixel in non-character area ■ax
n.

Here, the first threshold value generating means 3 generates the image x a
The threshold value Bh for binarizing sin information is, for example, Bh − (D
+D ) /2■aX ■in It is configured to dynamically calculate. The threshold value Bh, which is dynamically determined in accordance with the image information in this way, is given to the selection means 5 as the first threshold value. Further, the second threshold value generating means 4 is composed of a memory storing dither pattern information (dither matrix), for example, and outputs the information to the selecting means 5. This dither pattern information (dither matrix) is given, for example, as a matrix pattern of threshold values as shown in FIG.

Then, the threshold value Bh or the dither pattern is selectively extracted via the selection means 5 which is switched and driven based on the discrimination determination result by the comparison circuit 26 mentioned above, and is applied to the comparison means 6 to provide the binary value of the image information. Processing is performed.

The above-mentioned identification process, which is a characteristic part of this apparatus, will be explained in more detail with reference to FIGS. 2 to 7.

FIG. 2 shows a maximum value/minimum value detection circuit 20 in the identification means 2.
This shows the configuration of .

Now, when image identification processing is performed on an area of (8×8) pixels, a 4-line buffer is used as the line buffer l. The image information of 8 bits per pixel stored in this 4-line buffer 1 is input in parallel in columns for 4 lines to the selector 20a in accordance with the clock CLK of a predetermined period, as shown in the timing chart in FIG. .

The selector 20a receives the output signals SEo, S of the 2-bit counter 20b which operates by inputting the clock CLK.
Operates under the control of E 1, that person's capo) 1o, ~
The input data of I3 is output to the output port group AO, ~A3. BO,
-B3, Co, -C3, Do, and -D3 are sequentially and selectively output. Each output port group of this selector 20a is Ao, ~A3, Bo, ~B3, Co,
The data selectively output from ~C3, Do, and ~D3 is sent to the comparator 20c.

20d, 20e, and 20f, respectively. Specifically, as shown in FIG. 4, the data of the 4 pixels in the (J-1) column is given to the comparator 20c, and the data of the 4 pixels in the ('') column is given to the comparator 20d. The data of each of the four pixels in column J+2) is applied to comparators 20e and 20f, respectively. These comparators 20e, 20d, 20e, 2O
f' is used to compare the density values of four pixels in the column direction given from the selector 20a, and the maximum and minimum values thereof are determined and extracted. These comparators 2
The maximum density value d and the minimum density value d among the four pixels in the column direction are determined by 0c, 20d, 20e, and 20f, respectively.

The next stage comparators 20g and 20h are the above-mentioned comparators 20c and 2.
0d.

Maximum concentration values found at 20e and 20f, respectively'
sax and the minimum density value d are compared with each other in four columns in the row direction, and the maximum value D and minimum value aX D are respectively determined.

win As described above (4X4
) The maximum density value D and the minimum density value D within a predetermined range of pixels are determined and wax
It will be a win. Then, the subtraction circuit 21 calculates the maximum density difference ΔD from the maximum density value D and the minimum density value aX D at the timing shown in FIG.
n wax
At the timing of , the division circuit 22 calculates the maximum concentration difference ΔD.
standard wax normalized by the average density value D
The maximum a concentration difference ΔD is determined. Then, the comparison circuit 2B discriminates the normalized maximum concentration difference ΔD using a predetermined threshold Th at the next timing, and obtains selection information for selecting the axn 1 or the second threshold.

On the other hand, FIG. 6 shows an example of the configuration of the average value calculation circuit 23 in the identification means 2. In FIG. The selector 23a operates in the same manner as the selector 20a in the maximum value/minimum value detection circuit 20 described above under the control of the counter 23b. Therefore, in terms of hardware, the selector 23a and counter 23b are replaced by the aforementioned selector 20a and counter 20b.
It is also possible to have a shared configuration with

Therefore, each output port group A o +~ of the selector 23a
AS, Bo, ~B3, Co, ~C3, Do, ~
The data selectively output from D3 is sent to adders 23c and 2.
3d, 23e.

23r respectively. Specifically, as shown in FIG.
The data of the 4 pixels in the (j) column are given to an adder 23d, and the data of 4 pixels each in the (Jul) and (J+2) columns are given to adders 23e and 23f, respectively. These adders 23c, 23d, 21e, and 23f each calculate the sum ADDI of the density values of the four pixels in the column direction. The sum ADDI of the density values in the column direction obtained by these adders 23e, 23d, 23e, and 23r is input to the next stage adder 23g, and is added over four columns in the row direction. Through this two-stage addition process, the sum ADD2 of the density values within the predetermined range of (4×4) pixels described above is obtained. The sum ADD2 of the density values is then given to the divider 23h at the next timing, and is divided by the number of pixels within the predetermined range to obtain the average density value D.sub.2.

The average density value obtained in this way is given to the above-mentioned division circuit 22 as a reference density within that range.

(According to the present apparatus configured in this way, even if an image portion with a small maximum density difference value ΔD−aX and low contrast is detected, the maximum density difference value ΔD is set as the reference density p of that area. Normalize with -aX
Since this normalized density value difference ΔD is determined to determine whether the image area is a text portion or a photograph portion, the image type can be accurately identified.

Specifically, even if the image part has low contrast, it effectively utilizes the property that if the image is a photograph, the density is high overall, and conversely, if the image is text, the density is low overall. The image type can then be identified.

As a result, it is possible to reliably determine the low-contrast character image as a character portion, and to set an appropriate threshold for binarizing the character portion. In addition, low-contrast photographic images can be reliably determined as photographic parts, and appropriate thresholds (
(dither threshold) can be set.

Therefore, even if a document image contains multiple types of information, the text can be binarized with high resolution.
Furthermore, the photographic area can be binarized with good gradation. Moreover, selection control of the threshold value is very simple, and effects such as high control reliability can be achieved.

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. Further, the means for adaptively generating the threshold value can be modified in various ways, and the dither pattern used for binarizing the photographic area is not particularly limited.

Further, the size of the dither matrix is not limited, and the dither fist 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). .

Furthermore, although an example has been described in which the reference density for normalizing the maximum density difference within a predetermined range is calculated as the average density, it is also possible to use the maximum density value or the minimum density value as is.

Furthermore, it is also possible to set the region for determining the reference density to be larger so as to include the predetermined range. 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 image information is normalized by the reference density in the area where 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 result of this determination, the character part has good resolution (binarization is possible, regardless of its contrast). In addition, the photographic area has good gradation (binarization is possible, etc.), which has great practical effects.As a result, the two
Great effects such as being able to obtain valued images with high quality and improving processing efficiency can be achieved.

[Brief explanation of the drawing]

FIG. 1 is a schematic configuration diagram of main parts of an image processing device according to an embodiment of the present invention, FIG. 2 is a diagram showing a detailed configuration example of a maximum value/minimum value detection circuit in the embodiment device, and FIG. 3 is a processing diagram. FIG. 4 is a diagram schematically showing the concept of the pixel area of the target image; FIG. 4 is a diagram showing the processing operation timing for calculating the maximum density difference in the embodiment apparatus; FIG. 5 is a diagram showing an example of a dither pattern; FIG. 7 is a diagram showing a detailed configuration example of the average value calculation circuit in the embodiment apparatus, and FIG. 7 is a diagram showing the operation timing of the average value calculation process. FIG. 8 is a diagram showing an example of a document image to be processed, and FIG. 9 is a diagram showing the density level of a typical image signal of the image to be processed shown in FIG. ■ Line buffer, 2 Identification means, first threshold generation means, 4 second threshold generation means, 5° selection means, 6 comparison means, 20... Maximum value/minimum value detection circuit, 21... Subtraction circuit, 22... Division circuit, 23... Average value calculation circuit, 26... Comparison circuit. Applicant's agent Patent attorney Takehiko Suzue 2.3a Figure 6

Claims (1)

[Claims] means for determining a maximum density difference from image information within a predetermined range; and means for determining one of the average density, maximum density, and minimum density of image information within an area including the predetermined range with respect to the image information within the predetermined range. means for determining the reference density; means for normalizing the maximum density difference using the reference density; and determining the normalized density difference and binarizing the image information within the predetermined range according to the result of this judgment. An image processing device comprising means for setting a threshold value.