Application of improved maximum between-class variance method in tongue crack recognition
A technology with the largest variance and cracks between classes, applied in the computer field, can solve problems such as increasing the recognition range, and achieve the effect of accurate recognition and convenient tongue image teaching
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[0014] Examples of the present invention provide a crack feature recognition and denoising method of tongue image, such as figure 1 shown, including the following steps:
[0015] Step 1: Get a standard tongue map, such as figure 2 ;
[0016] Step 2: Copy the tongue map to get two identical images image1 and image2, and partition the two images, such as image 3 ;
[0017] Step 3: Use the OSTU method to filter each small area of the two images separately;
[0018] Step 4: merge images, merge;
[0019] Step 5: Denoise, reduce interference, and obtain the tongue map after crack identification, such as Figure 4 ;
[0020] Step 6: Extract crack features, including the number of cracks, crack length, such as Figure 5 .
[0021] The above steps will be described in detail below.
[0022] In the example of the present invention, it is assumed that the current tongue map is already a standard tongue map that has undergone tongue contour checking and tongue body extraction...
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