Adaptive fuzzy C-means image segmentation method based on potential function
An adaptive fuzzy and average image technology, applied in the computer field, can solve the problems of not getting better segmentation results, complicated and time-consuming calculations, and slow segmentation speed, etc.
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[0064] Attached below figure 1 The specific implementation steps of the present invention are further described in detail.
[0065] Step 1. Input the image to be segmented. In the embodiment of the present invention, the image to be segmented is input by the WINDOWS XP system, and the gray distribution matrix of the pixel points of the image is obtained.
[0066] Step 2. Obtain the histogram potential function and the maximum residual height of the image to be segmented
[0067] Using the normalized grayscale statistical histogram of the image to be segmented, the potential function of the histogram of the image to be segmented is calculated by the following formula:
[0068] P ( k ) = Σ i = 0 255 H ( i ) / ( 1 ...
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