Self-adaptive image segmentation method based on fuzzy threshold value

Abstract

The invention belongs to the technical field of image processing and in particular relates to a self-adaptive image segmentation method based on a fuzzy threshold value. The self-adaptive image segmentation method comprises the following steps: step 1, pre-processing a histogram to acquire an image histogram with double-peak properties; step 2, carrying out gradient detection on the pre-processed image histogram and determining the position of a wave trough; step 3, determining the position of a wave peak according to the position of the wave trough; step 4, determining the distance between two adjacent wave peaks according to peak values of the wave peaks; calculating window width sizes of membership functions of different images according to the distances between the different wave peaks; and step 5, determining a segmentation threshold value. The self-adaptive selection of the window width is realized, and the disadvantage that the segmentation of images on the histogram with inconspicuous double peaks cannot be easily realized by the fuzzy threshold value is effectively improved, an applicable range of the fuzzy threshold value image segmentation method is expanded, and the segmentation effect of the fuzzy threshold value segmentation method is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an adaptive image segmentation method based on fuzzy threshold. Background technique [0002] Image segmentation refers to the technology and process of dividing an image into non-overlapping regions and extracting objects of interest. There are three different approaches to image segmentation, one is the pixel clustering method that divides each pixel into the corresponding object or region, that is, the region method; the other is the boundary method that realizes segmentation by directly determining the boundaries between regions; the third is It first detects the edge pixels, and then connects the edge pixels to form a boundary to form a segmentation. [0003] In the image segmentation technology, the most commonly used is the image segmentation by thresholding. The threshold segmentation algorithm based on pixel histogram is a representative and very i...

AI Technical Summary

Problems solved by technology

In the prior art, the window width is calculated by comparing the number of extreme points of the fuzzy rate curve with the number of known pixel categories of the image, but this method has a poor segmentation effect on images whose image histograms have a single-peak distribution or bimodal distribution is not obvious. It is easy to cause the segmentation to fail

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