结合灰色理论和粒子群算法的归一化图像分割  

Normalized cut segmentation approach of grey theory and particle swarm optimization algorithm

作　　者：翟艳鹏[1] 郭敏[1] 马苗[1] 贺姣[1] 

机构地区：[1]陕西师范大学计算机科学学院,西安710062

出　　处：《计算机应用研究》2011年第2期776-778,共3页Application Research of Computers

基　　金：国家自然科学基金资助项目(10974130;60803088);中央高校基本科研业务费专项资金资助项目(GK200901006)

摘　　要：为了对多目标图像进行有效分割,使用灰色关联分析来衡量像素点间的相似性,并将normalized cut准则推导为双阈值分割准则,最后使用粒子群算法优化该准则,得出最佳的分割阈值。实验表明该方法计算速度快,能有效分割多目标图像。In order to deal with multi-object image effectively,the paper used grey relation grade to measure the similarity between different pixels,and transformed the normalized cut criterion into the dual-threshold segmentation criterion,then optimized the criterion using particle swarm optimization algorithm to get the best thresholds.Experiments show that the method has less segmenting time and can segment the multi-object image accurately.

关 键 词：灰色关联度 归一化划分准则 粒子群算法 双阈值图像分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]