Image Segmentation based on Two -dimension Fuzzy Tsallis-Entropy

摘要：

Image processing bears some fuzziness in nature, as a effective mathematical tool for handling the ambiguity, Fuzzy set theory is introduced in the paper to define a new kind of fuzzy entropy, namely Two-dimension Fuzzy Tsallis Entropy(TFTE) and applied in image segmentation following the maximum entropy principle. To overcome the huge calculational burden when generalizing one-dimension entropy to twodimension, the particle swarm optimization (PSO) algorithm was employed to accelerate the search of the optimal threshold. The validity and effectiveness of the presented method is illustrated by experiments and the application of Tsallis Entropy is generalized to fuzzy fields.

关键词： Image segmentation Two-dimension Fuzzy Tsallis Entropy(TFTE) Particle swarm optimization (PSO) Mazimum entropy

作者: Shu-Hong Yang Dong-Xue Xia Chun-Gui Li Zeng-Fang Zhang

作者单位: Department of Computer Engineering,Guangxi University of Technology Liuzhou,Guangxi 545006,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2871-2874

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）