Algorithm of Thermal Image Segmentation Based on Gaussian Mixture Model and Artificial Fish Swarm Algorithm

摘要：

The accurate thermal image segmentation becomes extremely challenging in the complex background conditions, especially in the circumstances that the foreground target and the background are very similar. The paper uses the Gaussian mixture model (GMM) for the rough segmentation in the temporal domain to solve the problem of complex background, then for the fine segmentation in the spatial domain by using 2d fuzzy partition maximum entropy method in order to overcome the difficulties of accurate segmentation in the case of the foreground target and background are very similar, and introduces the artificial fish swarm algorithm (AFSA) to search the combined parameters of segmentation quickly. Simulation results show that this algorithm is robust, good real-time, and achieved good segmentation effect

关键词： Artificial Fish Swarm Algorithm(AFSA) Gaussian Mixture Model (GMM) Thermal image segmentation

作者: TAN Jian-hui

作者单位: Faculty of Automation, Guangdong University of Technology Guangzhou, China

会议类型: 国际会议

会议名称: The 13th IEEE Joint International Computer Science and Information Technology Conference(2011年第13届IEEE联合国际计算机科学与信息技术会议 JICSIT 2011)

会议地点: 重庆

会议语种:英文

页码: 159-163

在线出版日期: 2011-08-20（万方平台首次上网日期，不代表论文的发表时间）