Image Segmentation Based on Improved PSO

摘要：

The multilevel thresholds image segmentation method based on maximum entropy and improved particle swarm optimization (PSO) is presented in this paper. The proposed algorithm takes advantage of the characteristics of particle swarm optimization, and improves the parameter and evolutional process of basic PSO. Compared with the basic PSO method, the proposed method can get the better optimal thresholds and more ideal segmentation result with less computation cost and has good search stability in the experiments. The experimental results indicate that the proposed method is an promising and efficient segmentation method with fast convergence and high computational efficiency.

关键词： particle swarm optimization(PSO) maximum entropy multilevel threshold image segmentation

作者: Tang Hongmei Wu Cuixia Han Liying Wang Xia

作者单位: School of Information Engineering, Hebei University of Technology, Tianjin, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 191-194

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）