A Novel Algorithm by Incorporating Chaos Optimization and Improved Fuzzy C-Means for Image Segmentation

被引：0
|
作者：
Zhu Z.-L. [1 ,2 ,3 ]
Liu Y.-J. [1 ,3 ]
机构：
[1] School of Information Engineering, Heibei GEO University, Shijiazhuang, 050031, Hebei
[2] Hebei Key Laboratory of Optoelectronic Information and Geo-Detection Technology, Shijiazhuang, 050031, Hebei
[3] Laboratory of Artificial Intelligence and Machine Learning, Heibei GEO University, Shijiazhuang, 050031, Hebei
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2020年 / 48卷 / 05期
关键词：
Chaos optimization; Fuzzy clustering; Image segmentation; Unequal cluster sizes;
D O I：
10.3969/j.issn.0372-2112.2020.05.019
中图分类号：
学科分类号：
摘要：
The spatial generalized fuzzy c-means clustering algorithm (GFCM_S) is a popular technique for image segmentation, but it is not so effective when the image has the features of unequal cluster sizes or the initial cluster centers we choose are improper. In this paper, for solving the above shortcomings of GFCM_S, a novel algorithm incorporating chaos optimization and improved fuzzy c-means (CIGFCM_S) is proposed. Firstly, each size of clusters is integrated into the objective function of GFCM_S so as to equalize the contribution of larger and smaller clusters to the objective function. Secondly, the iteratively membership degree and cluster centers are deduced by the Lagrange multiplier method. Thirdly, a new iterative strategy is used to seek the optimal solutions. In detail, the optimal solutions of next generation are searched by two-paths, one path originates chaos optimization and the other is obtained by updating membership degree and cluster centers on the basis of current optimal solutions, and then the better solutions go to next generation until the end. Lastly, the non-destructive testing (NDT) images with the characters of unequal cluster sizes are used for experiments, the results show that the proposed algorithm has better segmentation accuracy and visual effects. © 2020, Chinese Institute of Electronics. All right reserved.
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页码：975 / 984
页数：9
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