Image segmenting method based on dynamic multi-population integrated differential evolution algorithm
A differential evolution algorithm and image segmentation technology, applied in image analysis, image data processing, calculation, etc., can solve problems such as easy to fall into local optimum and weak local search ability of population
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[0053] Such as figure 1 As shown, the present invention is based on the image segmentation method of dynamic multiple clustering into differential evolution algorithm, comprises the following steps:
[0054] Step 1. Set the image segmentation threshold range and the fitness function for evaluating the segmentation effect:
[0055] The image to be segmented is a grayscale image, and the segmentation threshold range is set between 0-255;
[0056] In order to obtain the optimal threshold, the present invention uses the maximum variance between classes as the fitness function for evaluating the segmentation effect. The maximum inter-class variance is an effective evaluation index for image threshold segmentation, which can effectively obtain the optimal threshold f. The calculation formula is as follows:
[0057] f=w 0 ·w 1 ·(u 0 -u 1 ) 2 (1)
[0058] Among them, w 0 is the grayscale probability of the image background, w 1 is the gray level probability of the image tar...
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