Image segmentation method and system based on effectiveness index of fuzzy clustering guided by three-degree separation
A technology of image segmentation and fuzzy clustering, which is applied in image analysis, image data processing, character and pattern recognition, etc., can solve problems such as unsatisfactory effect and failure to consider data structure, and achieve accurate judgment of clustering number and clustering results accurate effect
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[0063] In this example, if figure 1 As shown, an image segmentation method for the validity index of fuzzy clustering guided by three-degree separation is carried out according to the following steps:
[0064] Step 1. Use the fuzzy C-means clustering algorithm to set {x 1 ,x 2 ,...,x i ,...,x N} are divided into K classes, and the membership degree matrix U={μ ik | i=1,2,...,N;k=1,2,...,K} and cluster center V={v 1 ,v 2 ,...,v k ,...,v K}; where x i Indicates the i-th pixel in the image X, μ ik Represents the i-th pixel x i Belongs to the kth class C k The membership value of , and 0≤μ ik ≤1, v k Represents the cluster center of the kth class; i=1,2,...,N; k=1,2,...,K; N represents the number of pixels in the image X;
[0065] Set the maximum number of iterations as M, the termination condition error of iterations as ε, and initialize K=2;
[0066] Step 2. Use formula (1) to construct the iter-th iteration objective function of the FCM fuzzy algorithm
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