文献类型：期刊文献

英文题名：Maximum variance image segmentation based on improved genetic algorithm

作者：Wang, Chun-Mei[1,2]; Wang, Su-Zhen[3]; Zhang, Chong-Ming[2]; Zou, Jun-Zhong[1]

机构：[1] College of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China; [2] Dept. of Electronics Engineering, Shanghai Normal University, Shanghai 201418, China; [3] College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266510, China

年份：2007

卷号：2

起止页码：491

外文期刊名：Proceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing

收录：EI(收录号：20074110862596)

语种：英文

外文关键词：Genetic algorithms - Optimization - Parameter estimation

摘要：An image segmentation method based on the OTSU and improved genetic algorithm (GA) is presented. The OTSU is taken as evaluation function and the segmentation problem is turned to the optimization problem. That is, GA efficiently searches the segmentation parameter space in order to obtain the optimal threshold. On the other hand, to overcome some limitation of GA, elite reinsertion is applied. The experimental results indicate that the method can not only obtain a better result, but also shorten the processing time. ? 2007 IEEE.