Open AccessResearch on Image Segmentation Method Based on Fuzzy Clustering
Author(s) -
Guangcai Feng
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012064
Subject(s) - segmentation based object categorization , artificial intelligence , image segmentation , scale space segmentation , image texture , minimum spanning tree based segmentation , pattern recognition (psychology) , region growing , computer science , computer vision , segmentation , range segmentation , fuzzy logic , cluster analysis , mathematics
Image segmentation is to divide an image into several continuous non-overlapping regions with similar characteristics, such as gray level, color and texture information. Through image segmentation, we can extract specific objects from complex background. The image has great uncertainty and fuzziness. Traditional segmentation methods often fail to achieve ideal segmentation effect, which directly affects the subsequent target feature extraction and result analysis. However, the fuzzy theory can well describe the characteristics of the image. Therefore, more and more scholars have studied image segmentation and proposed various related segmentation methods. Firstly, this paper analyses the hierarchical structure of image engineering. Then, this paper analyses the basic concepts of the fuzzy clustering algorithm. Finally, this paper analyses the image segmentation effect of the fuzzy algorithm by experiments.