%0 Journal Article
%T Image thresholding segmentation based on two-dimensional minimum Tsallis-cross entropy<br>基于二维最小Tsallis交叉熵的图像阈值分割方法
%A Tang Ying-Gan
%A Di Qiu-Yan
%A Zhao Li-Xing
%A Guan Xin-Ping
%A Liu Fu-Cai
%A <br>唐英干
%A 邸秋艳
%A 赵立兴
%A 关新平
%A 刘福才
%J 物理学报
%D 2009
%I 
%X Image thresholding segmentation method based on two-dimensional minimum Tsallis-cross entropy is proposed by utilizing the non-extensive property of Tsallis entropy in the paper. Firstly, the two-dimensional Tsallis-cross entropy is given, then the particle swarm optimization is used to search the best two-dimensional threshold vector by minimizing the two-dimensional Tsallis-cross entropy. The proposed method not only considers the spatial information of pixels, but also the interaction between the object and the background. Its segmentation performance is superior to thresholding methods using Shannon entropy and minimum one-dimensional Tsallis-cross entropy. Experimental results show that the proposed method can give good segmentation results with less computation time.
%K Tsallis-cross entropy
%K two-dimensional histogram
%K particle swarm optimization
%K image segmentation<br>Tsallis交叉熵，
%K 二维直方图，
%K 粒子群优化算法，
%K 图像分割
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=407D748E26A4FA490BC02E058155410D&yid=DE12191FBD62783C&vid=9FFCC7AF50CAEBF7&iid=CA4FD0336C81A37A&sid=9CF7A0430CBB2DFD&eid=23CCDDCD68FFCC2F&journal_id=1000-3290&journal_name=物理学报&referenced_num=6&reference_num=0