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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Multilevel Thresholding Based on Exponent Gray Entropy and Niche Chaotic Particle Swarm Optimization
verfasst von : Yi Shen, Yiquan Wu, Yang Ji
Erschienen in: Foundations of Intelligent Systems
Verlag: Springer Berlin Heidelberg
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The method of threshold selection based on maximal Shannon entropy or exponent entropy only depend on the probability information from gray image histogram, and don’t immediately consider the uniformity of the gray scale within the cluster. Considering these facts, thresholding based on exponent gray entropy is proposed. Firstly, exponent gray entropy is defined and the method of single threshold selection is given. Then, the method is extended to multilevel thresholding. Furthermore, the niche chaotic mutation particle swarm optimization algorithm is adopted to find the best multi-threshold. Many experimental results show that, compared with multilevel thresholding based on maximal entropy and particle swarm optimization, the proposed segmentation method has less operation times and segmented images of the suggested method are more accurate in edge and texture.