Image segmentation based on equivalent three-dimensional entropy method and artificial fish swarm optimization algorithm

作     者：Lei, Xiangxiao Ouyang, Honglin Xu, Lijuan 

作者机构：Hunan Univ Coll Elect & Informat Engn Changsha Hunan Peoples R China Changsha Social Work Coll Sch Elect Informat Engn Changsha Hunan Peoples R China 

出 版 物：《OPTICAL ENGINEERING》 (Opt Eng)

年 卷 期：2018年第57卷第10期

页      面：1-7页

核心收录：

学科分类：08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 081102[工学-检测技术与自动化装置] 0811[工学-控制科学与工程] 0702[理学-物理学] 

基　　金：National Natural Science Foundation of China 

主　　题：image segmentation maximum entropy three-dimensional histogram optimization algorithm artificial fish-swarm algorithm 

摘      要：To improve the timeliness of the three-dimensional (3-D) maximum entropy method, an image segmentation method based on equivalent 3-D entropy and artificial fish swarm optimization algorithm is proposed. An equivalent 3-D entropy method without logarithmic operation is developed, and its equivalence is proved theoretically. The optimal threshold is determined based on the artificial fish swarm optimization algorithm so as to avoid exhaustive search and improve algorithm efficiency. The experimental results demonstrate that the proposed method is more time-efficient than the traditional 3-D entropy method and the equivalent 3-D entropy method without affecting segmentation. Compared with the one-dimensional entropy method and the two-dimensional entropy method, it is obviously superior in noise immunity and detail preservation. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)