南方医科大学学报2012，Vol.32Issue(5)：655-658,663,5.DOI:10.3969/j.issn.1673-4254.2012.05.015
一种改进的自适应谱聚类图像分割算法
An improved adaptive spectral clustering for image segmentation
摘要
Abstract
Objective To propose an improved adaptive spectral clustering method for image segmentation to allow automatic selection of the optimal scaling parameters and enhance the accuracy of spectral clustering.Methods Using constrain conditions for optimizing the criterion function and determining the optimal scaling parameters by iteration,the final image segmentation was achieved through spectral clustering based on Nystr(o)m approximation.We chose suit weight functions for different texture images,and used the proposed method for image segmentation.The k-means algorithm and the method of spectral clustering after pre-segmentation by manually choosing the scaling parameter were compared with the proposed method.Results The improved spectral clustering algorithm with automatic selection of the optimal scaling parameters achieved better results of image segmentation than the other two methods.Conclusion The proposed algorithm can improve the accuracy of spectral clustering for image segmentation.关键词
谱聚类/图像分割/自适应/Nystr(o)m估计Key words
spectral clustering/image segmentation/adaptive/Nystrom approximation分类
信息技术与安全科学引用本文复制引用
陈姿羽,黄靖,李伟鹏..一种改进的自适应谱聚类图像分割算法[J].南方医科大学学报,2012,32(5):655-658,663,5.基金项目
国家自然科学基金(81000642) （81000642）
