FCM image segmentation method and apparatus

Abstract

The present invention relates to a FCM image segmentation method and apparatus, and solves the technical problem of failure of effective completion of image segmentation by a general fuzzy clustering method. The initialization process includes: forming a set S1 of weighted local grayscale items of all neighborhood points relative to sample points; and the iteration process comprises: in current iteration, forming a set S2 of weighted local distance items of the current iteration of all the neighborhood points relative to the sample points through grayscale value differences between the neighborhood points of the sample points and a clustering center Viter-1 of previous iteration, the membership Uiter-1 of the previous iteration and a spatial Euclidean distance, and forming the membership Uiter of the current iteration through the set S1 of the weighted local grayscale items, the set S2 of the weighted local distance items of the current iteration, and the clustering center Viter-1 of the previous iteration; and forming the clustering center Viter of the current iteration according to the membership Uiter of the current iteration.

Description

technical field [0001] The invention relates to an image segmentation method and device, in particular to an image segmentation method and device for fuzzy clustering segmentation. Background technique [0002] Image segmentation is an important process in image processing and computer vision. Image segmentation is the technology and process of dividing an image into several specific regions with unique properties and proposing objects of interest. The fuzzy clustering method (that is, the FCM algorithm) in the clustering and segmentation method has been successfully used in various aspects such as medical image processing, artificial intelligence, and pattern recognition. [0003] The FCM algorithm adds a membership function on the basis of hard classification, so that each sample point no longer belongs to a certain class, but belongs to a different class with a certain percentage. The objective function of the FCM algorithm is as follows: [0004] [0005] N represe...

AI Technical Summary

Problems solved by technology

[0007] In view of this, the purpose of the embodiment of the present invention is to provide a FCM image segmentation method and device to solve the technical problem that the fuzzy clustering method cannot effectively complete image segmentation in a relatively high noise environment

Images