彩色图象分割  

Color Image Segmentation

作　　者：郭国栋 马颂德[1] 

机构地区：[1]中科院自动化所模式识别国家重点实验室

出　　处：《中国图象图形学报（A辑）》1998年第11期918-921,共4页Journal of Image and Graphics

摘　　要：提出一种在特征空间进行非监督学习的新技术。以信息理论观点，把特征空间看成是两个不同的源所组成，即“峰（ｍｏｄｅ）”和“谷（ｖａｌｅｙ）”。一个熵门限被用来自动区分特征空间中的不同单元。那些标号为“峰”的单元被连接起来形成峰的区域。提出一个修改的Ａｋａｉｋｅ信息准则来求解相应的聚类有效化问题。当所有必需的参数都估计出来以后，将一个基于多数博弈论演化而来的标号算法用于求解分割所对应的优化问题。新方法应用到彩色图象的分割问题中。A novel technique for unsupervised learning in feature space is presented. The feature space is considered as composed of two distinct sources, “mode” and “valley”, in the point of view of information theory. An entropy based threshold is taken to distinguish the discrete cells in the feature space. The cells labeled as “mode” are then chained to form mode areas. Thereafter a modified Akaike’s information criterion is proposed to solve the cluster validity problem. After all the parameters are estimated, a labeling algorithm is developed based on the majority game theory. The method is applied to color image segmentation. The segmentation process is completely autonomous.

关 键 词：彩色图象 非监督学习 参数估计 图象分割 特征空间分析 多数博弈论 图象分割 

分 类 号：TN911.73[电子电信—通信与信息系统]