光学精密工程2009，Vol.17Issue(7)：1665-1671,7.
应用聚类和分形实现复杂背景下的扩展目标分割
Segmentation for extended target in complex backgrounds based on clustering and fractal
摘要
Abstract
A new segmentation algorithm which was divided into two steps was proposed for an extended target in complex backgrounds by utilizing the K-means clustering and fractal theory. Firstly, the K-means clustering algorithm was improved by using the rough set theory to determine initial cluster centroids. On the basis of K-means clustering segmentation and region connection, the edges of the target and backgrounds were extracted accurately and intactly. After boundary tracking, the potential target regions were detected according to the characteristics of the extended target. Secondly, by giving the function of a fractal dimension changing with the scale, the natural backgrounds in potential target regions were removed by the fractal scale invariance. Then,the background conglutination was eliminated by a mathematical morphology method. The experimental results indicate that the algorithm can segment the extended target in complex backgrounds correctly and reliably, and the segmented target reserves a good contour.关键词
图像分割/扩展目标/K-均值聚类/分形/粗糙集Key words
image segmentation/extended target/K-means clustering/fractal/rough set分类
信息技术与安全科学引用本文复制引用
张坤华,杨烜..应用聚类和分形实现复杂背景下的扩展目标分割[J].光学精密工程,2009,17(7):1665-1671,7.基金项目
国家自然科学基金资助项目(No.60572101) （No.60572101）
深圳大学科研启动基金资助项目(No.200745) （No.200745）
国家重点实验室基金资助项目(No.51483040105QT5118) （No.51483040105QT5118）
深圳市科技计划基金资助项目 （）
