计算机工程与应用Issue(18)：151-155,223,6.DOI:10.3778/j.issn.1002-8331.1412-0334
基于分水岭的多目标核聚类图像分割
Multi-objective kernel clustering image segmentation based on water- shed over-segmentation
摘要
Abstract
The traditional clustering-based image segmentation generally only utilizes the gray information of the image. In order to better use the region and edge information, a multi-objective fuzzy kernel clustering image segmentation algo-rithm based on watershed over-segmentation is proposed. The watershed method is used to over-segment the image and obtain some regions. Then the multi-objective fuzzy kernel clustering algorithm is used to cluster the representative points of the regions and the pixels on watershed. All the pixels of the image are labeled according to the clustering results of the region and the watershed to obtain the final image segmentation result. The experimental results show that the objective in the image can be more completely segmented from the background due to using the image region information.关键词
多目标进化算法/核聚类/图像分割/分水岭Key words
multi-objective evolutionary algorithm/kernel clustering/image segmentation/watershed分类
信息技术与安全科学引用本文复制引用
赵凤,韩文超,惠房臣..基于分水岭的多目标核聚类图像分割[J].计算机工程与应用,2015,(18):151-155,223,6.基金项目
国家自然科学基金（No.61102095，No.61202153）；陕西省自然科学基础研究计划资助项目（No.2012JQ8045，No.2014JQ8336）；陕西省科学技术研究发展计划资助项目（No.2014KJXX-72）；中央高校基本科研业务费专项资金资助（No.GK201503063）。 （）
