JPS59225481A - Picture processing method - Google Patents

Abstract

PURPOSE:To attain correction of area only with two times raster scanning by using only an area including an area separated by a threshold value of a level taken surely as an object among areas of a threshold value of a wave trough level as an object area. CONSTITUTION:An area separated by a threshold value T1 of a wave trough level (frequency) from a picture by the 1st raster scanning is numbered with a tag No. and the result is stored in the 1st tag memory 62. Simultaneously, the tag No. of the area separated by a threshold value T2 of a level becoming surely an object and including a part becoming surely an object area among the said areas is stored in a tag table 53. A tag No. output from the 1st tag memory 62 is converted at an area converting table 51 at the 2nd raster scanning and only the area corresponding to the tag No. stored in the tag table 53 is taken as the area of object and stored in the 2nd tag memory 61, thereby attaining the correction of area.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field to which the invention pertains] The present invention relates to an improvement in an image processing method for capturing an object with a TV camera and performing image measurement of the object from the image.

[Prior art]

When an object is captured by a color TV camera and the image of the object is measured, the object to be measured (e.g., red blood cells, white blood cells, nucleus, cytoplasm, etc.) from the image (e.g., blood image). It is most basic and important to accurately separate the

In order to separate the regions of the target object, there is also a method of separating the target object from an image obtained using light of a wavelength where the absorption of the target object is sufficiently larger than that of other objects, using the spectral characteristics of the target object. Yes (U, 8 Patent 3,999,047
'Patent Publication No. 13305-1980) is
In this case, a special optical filter is required, a general-purpose color TV camera cannot be used, and the SIN is poor.

In the case of a method using a general-purpose color TV, an image that has been subjected to a linear operation with a normal power of 2- is binarized using an appropriate threshold value to divide the image into regions. In this case, as the darkness value, the density histogram of the image as shown in FIG. 1 is taken, and the color calculation value T corresponding to the valley is usually adopted. However, in this case, since there is an overlapping portion in the density histograms of the object and the background, the frequency does not become O even at the threshold value T.

Therefore, even if the threshold value T of the valley part is used, it is not possible to accurately cut out the object, and there is a problem that part of the background is cut out as the object at the same time. In order to perform region separation, there is a method of performing region correction using two thresholds: a threshold T1 at a valley level (frequency) and a threshold T2 at a level that is definitely an object, as shown in FIG.

In other words, it is a method that reliably binarizes the target object, which is the darkness value, and then expands this binary image to the area where the valley level is the darkness value.This is a problem of so-called area filling, but for this purpose, the image must be Since the scan must be repeated several times and a judgment function is required to check whether the enlargement is completed each time the scan is performed, the configuration and software are complicated and the processing time is long.

[Purpose of the invention]

The present invention was made in order to solve the above problems, and it processes a gray scale image obtained by a TV camera, accurately separates the area of the object included in the image, and performs image processing with a short processing time. The aim is to implement the method.

[Summary of the invention]

The gist of the present invention to achieve the above object is image processing that processes an image signal obtained by a TV camera, separates the region of the object included in the image, and measures the feature amount of the object. In the apparatus, in the first rask scan, areas of the image separated by a first threshold value are numbered by tagging and stored in a first tag memory, and the areas are separated by a second darkness value. Store the tags of items that definitely include the target object area in the tag table, and
In the second rusk scan, the tag store output from the first tag memory is converted using an area conversion table, and only the area corresponding to the tag store stored in the tag table is set as an object area and transferred to the second tag memory. The image processing method is characterized in that area correction is performed using K when the image is stored.

〔Example〕

The present invention will be explained in detail below with reference to the drawings.

FIG. 3 is a configuration block diagram showing an embodiment of an image processing device for realizing the present invention. FIG. 4 is a block diagram illustrating a part of the operation of FIG. 3. 1
What is the general power of Kti in the case of each part of the image processing device? -TV
A to digitize the image signal from the camera) pixel by pixel
An image memory section 4 connects to the system path 1 and inputs and stores the digital image signal from the A/D converter 2.゛A calculation unit which inputs the digital image signal from the image memory unit 3 and performs color calculation and binarization for each pixel, 7
8 is connected to the system bus 1, and is an address pull counter that counts up the contents of the addressed counter to count a minute amount of c1% for each area and create a color calculation histogram; 8 is connected to the system bus 1; The details of each part are shown in FIG. 4.

Reference numeral 6 denotes a tag memory unit connected to the system bus 1, which stores type A to which each pixel of the color image belongs (black representing the type of area to which the pixel belongs is referred to below) and tag/I.
6 (hereinafter referred to as the A assigned to each area) 2
It consists of two tag memories 61 and 82. 5 is a tagging section connected to the system bus 1; In this tagging unit 5, the contents are written in 51 by the table write signal TV from the processor 8,
A new type signal TP2 and a new pit pattern output BP are generated in response to the type signal TPI and tag grave signal TGi for each pixel output from the tag memory 61 and the pit pattern output BPI from the arithmetic unit 4.
52 is a numbering circuit for numbering tag areas in correspondence with the pit pattern output BP2 from the area conversion table 51;

53 is the bit pattern signal BP 31 of the tag shop.
This is a tag table that stores the selected items.

The typewriter signal TP2 from the area conversion table 51 and the tagger output TG2 from the numbering circuit 52 are added to the tag memory 62 and stored therein. Figure 4 is the first
The state in which the second (A+) tag memory operates as the tag memory 62 and the second (A2) tag memory operates as the tag memory 61 is shown.

Next, its operation will be explained. It is assumed that the image to be segmented has already been input to the image memory. The image memory 3 is read out and a calculation unit 4 performs a linear combination calculation for each pixel. In the case of a color image, the optimal color calculation coefficient for region separation is (r+go b), and the image memory contents of a specific pixel are R, G.

If B, the color calculation value is e−r body R+gsG+bsB (1
). The color calculation value output from the calculation section 4 is applied to the addressable counter 7 to form a color calculation histogram as shown in FIG. 2 in the addressable counter. Processor 8 is addressable counter 7
Read the contents of and set the first threshold value T□ of the valley level of Hisdog 2m and the second darkness value T2 of the level that is definitely the object.
seek. For example, the minimum level MIN may be used as the threshold T2.

Next, the contents of the image memory 3 are read out by raster scan/return to the calculation unit 4, and the value of CL-e-71 (2) C2 so-called e-T2 (5) is determined for each pixel (the circuit that performs this calculation is There are 2), C1≦
When it is 0, BPI-1 (BPI-0 when C1>0).

When C2≦0, BP3maro1 (If “2> Q, then B
A bit pattern output BPi, BP3 corresponding to P3-0) is generated and added to the tagging section 5.

Data is written in advance to the area conversion table 51 by the processor 8, and the bit pattern output BP1-1
When the type output TP2 is type A I, when the bit pattern output BPI-00, the type output TP2 is type 0, and the bit pattern output BP2 is BP.
2-BP i and is added to numbered circuit 52.

The numbering circuit 52 inputs the bit pattern output BP2 and numbers the area portions, and the tagger output TG2 is stored in the tag memory A1 serving as the tag memory 62. At the same time, the tag A output TG2 is added to the tag table 53, t
and stores the tag shop output TG2 only when BP3-1 is reached. Figure 5 is an example of an image showing the state of area separation.
is the background, A1. A2. A3 is the area of tag shop 1, 2, and 3 separated by threshold T1, and A4 is threshold T
This is an area separated by 2. In this case, only tag shop 1 is stored in tag table 53. Next, tag memory 1 and /162 are exchanged, tag memory 1 is set as tag memory e1, tag memory 2 is set as tag memory 62, and the contents of the tag table 53 are read to the processor 8, and only the tag memory at this time is set. The contents of the area conversion table 51 are written to the table write signal T so as to remain as the target object.
Rewrite by V. In other words, in the example shown in FIG. 5, among the areas of type JK1 in the area conversion table 51,
Only tag shop 1 is a new type/I & 1 and Nasi, other tags 42
．． The area of 3 is a new type AO and is represented as a background.

Tag memory I61 for each pixel by raster scanning
The area correction is completed by reading out the contents of , converting it using the area conversion table 51 written as described above, and writing the output to the tag memory A2. As a result, the content written in the tag memory A2 stores only the area separated by the second threshold among the areas determined by the first threshold as the target object area.

Next, a case will be described in which the above embodiment is applied to processing of blood cell images. Here, a case is shown in which the image is separated into the background and blood cells, and then the blood cell region is separated into white blood cells and red blood cells. W-axis histogram of blood cell area (color calculation value ew-0-
28R+ O-50G-0-9'713) is pear, nucleus, and cytoplasm as shown in Figure 6.

Each peak of red blood cells appears. T1 is selected as the first threshold for separating white blood cells and red blood cells, and T2 at the valley between the nucleus and cytoplasm is selected as the second threshold to ensure white blood cells. The image when separated using the first threshold T1 is separated into a white blood cell area A71 and a red blood cell area A72 as shown in FIG. Separation is insufficient. Furthermore, a second threshold T2
By leaving only the region containing the region (nucleus) to be separated as white blood cells, the region is completely separated into a white blood cell region A81 and a red blood cell region A82, as shown in FIG. 8, and the effect of region correction becomes clear.

The image processing device configured as described above is faster in processing speed because it can perform area correction with only two rask scans, instead of repeating the same process over and over again as in the conventional method. composition.

The software is also simple.

Further, an external computer may be used as the processor 8 in the above embodiment. In this case, the processor 8 takes charge of the communication function with the external combination server.

In addition, on the upper A male side, the force 2 calculation coefficient can be freely set according to the color of the object, and the processor determines the optimal threshold value for each color image to perform region separation, so it is possible to adjust the conditions such as staining and light source. Regions can be separated accurately without being affected.

Furthermore, since the present invention can use a general-purpose color TV camera and is fast, it can be applied not only to blood cell images but also to pattern measurement and recognition of general industrial products.

Further, in the above embodiment, the case where a color TV camera is used has been described, but the present invention is not limited to this, and can be similarly used for black-and-white, dark and dark images, etc. In this case, the arithmetic unit may include only a binarization circuit, and the configuration of the image memory can be simplified.

〔Effect of the invention〕

As described above, according to the present invention, it is possible to realize a high-speed image processing device that can process a grayscale image obtained by a TV camera and accurately separate regions of objects included in the image. .

[Brief explanation of the drawing]

FIG. 1 is a conventional example of a density histogram of an image, FIG. 2 is a density histogram for explaining the present invention in detail, and FIG. 5 is a configuration block diagram showing an embodiment of an image processing apparatus implementing the present invention. FIG. 4 is a block diagram of the main part of a part of FIG. 3, FIG. 5 is an example image for explaining the state of region separation according to an embodiment of the present invention, and FIG. 6 is a diagram used for region separation of blood cells. FIG. 7 is an example of an image in which regions are separated using only the first threshold value, and FIG. 8 is an example of an image in which region correction is performed using the second threshold value. 51...Area conversion table, 53...Tag table, 61゜62...Tag memory, ■...Image signal, T
1...first threshold value, T...second threshold value, A71.
Ag3. Al...Area of the object, TGI, TG2
...tag output. Rhinoceros Figure 1 "Color operation term → Figure 2 Color) Calculated value e →

Claims (1)

[Claims] In an image processing device that processes an image signal obtained by a TV camera, separates the region of the object included in the image, and measures the feature amount of the object, in the first rask scan, the image is set to a first threshold value. The area separated by is numbered with a tag plate and stored in the first tag memory, and the tag foot of the area that is separated by the second threshold value and includes a portion that definitely becomes the target area is stored in the tag table. Then, in the second rask scan, the tag output from the first tag memory is converted using an area conversion table, and only the area corresponding to the tag stored in the tag table is used as the second object area. This image processing method is characterized in that area correction is performed by storing information in a tag memory.