JPS60136478A - Picture processor - Google Patents

Abstract

PURPOSE:To obtain a faithful reproduced picture by obtaining the value corresponding to the difference of density between picture elements adjacent to each other within each block and identifying accurately different image areas according to the obtained result. CONSTITUTION:An original picture is read by a scanner and stored temporarily to a picture memory GM after A/D conversion. The picture data in the memory GM undergoes the software processing by an exclusive microprocessor GP. The picture data in the memory GM is first divided into blocks of (8X8) picture elements, and the sum total S is obtained for the absolute values of difference of density between adjacent picture elements. It is identified whether the corresponding block is equal to a mesh image area, a character image area or a photoimage area according to the sum S. The subsequent picture processings are carried out by the result of identification of the block.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field] The present invention relates to an image processing device having an image identification function.

[Prior art]

Conventionally, in this type of digital image processing apparatus, the accuracy of identifying a read image of a document is not sufficient, so a series of image processing is performed on the entire image even after incorrect identification. Therefore, it has been impossible to completely reproduce all partial image areas for a document containing both photographs and text halftone images. In particular, since it is difficult to distinguish between the halftone image area and the text area, processing for the text image area is applied to the halftone image area, which has the disadvantage of greatly deteriorating the reproduced halftone image. Ta.

〔the purpose〕

The present invention was made in view of the above-mentioned problems, and it is possible to obtain a faithfully reproduced image by accurately identifying different image areas and performing appropriate image processing according to the image tone. It is an object of the present invention to provide an image processing device that has the following features.

〔Example〕

The present invention will be explained below based on the drawings.

First, the image tone identification algorithm according to the present invention will be described below in order of each step.

(Step 1) Read the original image with a scanner consisting of, for example, a CCD,
The read image is digitized to obtain a digital image. This digital image is divided into NXM blocks (where N indicates the number of pixels in the main scanning direction, and M indicates the number of pixels in the sub-scanning direction).

Here, the value of NXM is 16 pixels/■
For each scan, 8 is best.

That is, here, the image is divided into blocks of 8×8 pixels.

(Step 2) In each divided block, calculate the mutual density difference between adjacent pixels, and calculate the sum S of the absolute values. For example, in a block of NXM=8×8 pixels as shown in FIG. 1, the total sum S=455.

In the above example, since the density value is set to 00 to 15), the possible values of the sum S are S=0 to 1,6 depending on the image tone.
The range is 80.

(Step 3) Calculate the average value of pixel density in each of the divided blocks. In the example of FIG. 1, the average density value is #5.

(Step 4) The preset values P1 and P2 are compared with the sum S of the absolute values of the density differences obtained within each block, and images are identified for each block based on the following criteria. Let's do it.

i) When s≦P1 Photographic halftone image area 2) PI(S
When ≦P2 Character line image area 3) S) When P2 Halftone image area Here, PI<P2.

The above identification criterion is that the two-dimensional spatial frequency of the original is
This is based on the statistical property that the value decreases in the order of text>photograph, and the predetermined values P1 and P2 are values determined by the reproduction capability of the apparatus for text and halftone originals.

In this example, the sum S of the absolute values of the density differences between adjacent pixels is calculated, but it may be configured such that, for example, a predetermined calculation is performed on the density differences between adjacent pixels to obtain parameters according to the image tone. .

In any case, it is sufficient to obtain a value that allows two-dimensional determination of the ups and downs of image density.

(Step 5) Conclusion 3- identified in each block (step 4) It is converted into a binary image signal based on the result.

(5-1) If it is determined to be a photographic halftone image area, dither the image within the block. Here, dither processing is, for example, by comparing each threshold value of an 8×8 dither matrix with the density data of each pixel in a block to generate a binary signal °] °.
It refers to something that obtains °0°.

The dither matrix shown in Figure 2 is a concentrated dot type,
This is an example that has the ability to reproduce in 16 gradations. Therefore, the pixel density values shown in FIG. 1 are binarized using the threshold values in the corresponding dither matrix, and the white and black signals (
°, ゛0° signal).

(5-2) If it is determined that it is a character (line drawing) image area, complete binarization processing is performed using a fixed threshold (fixed threshold). In this example, the threshold value is 1/2 of the highest concentration level.
, that is, it is binarized at 7, but the ground color density in the block (
For example, good results can be obtained by setting the value according to the document image based on the lowest density within a block or the most frequently occurring density value obtained from a histogram.

(5-3) If it is identified as a halftone image area, replace each pixel density in the program with the average density obtained in (step 3), and perform dithering using the dithering machine shown in Figure 2. and binarize it. That is, the processing method executed when it is determined that the area is a halftone image area is the so-called density pattern method, and the dither matrix used here is preferably a dot concentration type. This is because by calculating the density average value for each block and applying dot concentration dither to this average value, it is possible to create a halftone image original with a high spatial frequency.
Binarization processing (unique pattern of dither matrix)
It is possible to suppress interference noise (generally generated as moiré fringes) caused by

Using the algorithm described above, one original document is binarized in near real time by repeating the processing block by block (step 5), and then imaged with a binary printer such as a laser beam printer (LBP). Can be played.

Next, an example of an image processing apparatus according to the present invention will be described.

The image processing apparatus in this embodiment performs the above-described image processing by computer processing, particularly software processing by a microcomputer dedicated to image processing having a multi-microprocessor structure. FIG. 3 is a block diagram of the configuration of an embodiment in this case. SC is CO for reading the original image.
A scanner consisting of D, GP a microprocessor dedicated to image processing, and PR a laser beam printer (LBP).

The original image is read by the scanner SC, and the read image signal is A/D converted by an A/D converter (not shown) and temporarily stored in the image memo IJGM.

The image data in the image memo 90M is then software-processed by the image processing dedicated microprocessor GP according to the image processing algorithm described above and converted into a binary signal, and the binary signal is output to the LBPPR. SP is
It is a microprocessor for controlling the entire system, SM is a program memory that stores the control contents, and GM is an image memory used in the image processing process.

FIG. 4 is a flowchart showing the procedure of image processing executed by the microprocessor GP. To explain the diagram, in (step to step 2) pixel data is extracted from the image memory GM 8.
A block of ×8 pixels is formed, and the process moves to (step 3). In step 3, as described above, the sum S of the absolute values of density differences between adjacent pixels within the block is calculated. Images are identified based on the sum S fitted in (step 4.5). When it is judged as 1NO° in (Step 4) and No'' in (Step 5), it is judged that the block is a halftone image area, and in (Step 6) the average density value of the block is calculated and the block Replace each pixel data within with the average density value. Then, (step 9
) performs dither processing on the block whose density has been smoothed. When it is determined that the result is "@NO" in (Step 4) and "YES" in (Step 5), it is determined that the block is in the character image area, and the process moves to (Step 7). In step 7, each pixel within the block is binarized by fixed closure.

7- If the determination is ``YES'' in (step 4), it is determined that the block is a photographic image area, and dither processing is performed on the block in (step 8). (Step 10) stores the binary data for each block obtained in (Steps 7 to 9) in the image memory GM.

In this example, the image memory GM stores at least 16 lines worth of multilevel density level pixel data and 1
It is assumed that six lines of binary data can be stored. Note that one line here indicates, for example, one main scanning result of a document read by a scanner. The memory area aL a2 is for storing pixel data sequentially read by the scanner SC and extracting this data in units of 8×8 pixels. That is, for example, pixel data from the scanner SC is sequentially written in the memory area a1 in the line direction, and from the memory area a2, the pixel data is written to the microprocessor GP.
Pixel data is extracted for each block of 8×8 pixels. Furthermore, for example, binary data is written in each block of 8 x 8 pixels by the microprocessor 8-processor GP to the 8 x memory area b1, and the already written pixel data (binary data) is written from the memory area b2. It is read out sequentially in the line direction. This read binary data is then output as a reproduced image by the printer PR. In this way, in this example, multiple microcomputers are used,
By performing parallel processing of pixel data, writing of multi-value density level pixel data and reading of multi-value density level pixel data for each block can be performed simultaneously, and writing of binary data for each block and continuous output of binary data can be performed simultaneously. This can be done simultaneously, and the parameter S can be calculated two-dimensionally at high speed, so the read pixel data can be processed and output almost in real time. The scanner SC and the printer PR are controlled by the microprocessor SP in synchronization with the operation of the microprocessor GP.

[Other Examples]

In the above embodiment, three types of binarization processing were applied to the image data by switching between them according to the identification results, but the same image data was processed in parallel using the three types of processing methods described above in advance to perform identification. By configuring the system to select one of the three types of binarized data based on the result, faster processing can be performed.

Further, according to the present invention, since the image is identified two-dimensionally, it is possible to accurately distinguish between the halftone image area and the character image area.

〔effect〕

As described above using the embodiments, according to the present invention, it is possible to accurately identify images, and therefore, it is possible to realize image processing according to each tone, so that images more faithful to the original can be realized. It is possible to obtain a reproduced image.

Further, according to the present invention, since the image is identified two-dimensionally, the halftone image area and the character image area can be particularly accurately identified.

[Brief explanation of the drawing]

Figure 1 is a density distribution diagram when a document is divided into blocks of 8 x 8 pixels, Figure 2 is a diagram showing a dither matrix,
FIG. 3 is a configuration block diagram of an embodiment of the image processing apparatus of the present invention, FIG. 4 is a flowchart showing the procedure of image processing in this embodiment, and FIG. 5 is a diagram showing the image memory GM. GM... Image memory GP... Dedicated microprocessor PR.
・・・・・・Lower beam printer SC・・・・・・
...Scanner SM...Program memory SP...
...Microprocessor Σ□

Claims (1)

[Claims] Divide the input image data into a plurality of blocks, calculate a value according to the density difference between adjacent pixels within each block, identify the image tone for each block according to the value, and distinguish between different images. An image processing device characterized in that it is configured to perform different processing on blocks of different colors.