中国空间科学技术2012，Vol.32Issue(2)：35-42,8.DOI:10.3780/j.issn.1000-758X.2012.02.006
基于改进核聚类算法的空间目标识别方法
Space Target Recognition Based on Improved Kernel FCM
摘要
Abstract
A recognition system was presented to accomplish space target classification. Firstly, Image feature vectors were extracted according to invariant region moments, shape and image descriptors of space objects. And then, clustering algorithm is applied to the classify space target. An improved kernel clustering algorithm based on Voronoi distance was proposed which had a crisper membership function and was robust for noise and outliers. Experiments show that the improved kernel fuzzy clustering algorithm is more accurate and valid than that of the conventional methods.关键词
图像识别/核聚类法/特征提取/空间目标Key words
Image recognition/Kernel cluster method/Feature extraction/Space target引用本文复制引用
王晓雪,杨永胜,敬忠良..基于改进核聚类算法的空间目标识别方法[J].中国空间科学技术,2012,32(2):35-42,8.基金项目
国家863高科技计划(2009AA7043005,2010AA7043005)资助项目 （2009AA7043005,2010AA7043005）
