基于减法聚类算法的视频运动目标定位  

Moving Object Location in Video Sequences Based on Subtractive Clustering Algorithm

作　　者：孙志海[1] 孔万增[1] 朱善安[1] 

机构地区：[1]浙江大学电气工程学院,杭州310027

出　　处：《光电工程》2008年第7期12-16,共5页Opto-Electronic Engineering

摘　　要：针对视频运动目标定位的需要,本文给出了一种新的视频运动目标定位方法。该方法运用减法聚类算法对视频运动目标进行定位。分析了减法聚类算法的原理,给出了减法聚类算法的公式推导,目标定位的实现步骤及流程框图。研究了本文方法对不同类型视频运动目标的定位效果,并与基于区域生长的定位方法进行了详细比较。结合实验数据说明了本文方法的定位过程、处理时间及抗噪性能。实验结果表明,本文方法适用于待定位视频序列二值图像存在较大噪声斑点或空域连通特性较差的场合。In order to meet the needs of moving object location in different video sequences, a novel moving object location method was proposed. Subtractive clustering algorithm was used for object location in video sequences. The theory of subtractive clustering algorithm was analyzed. Equations of subtractive clustering algorithm, software flowchart and realization steps of proposed method were presented. Different location results for different video sequences were studied. Subtractive clustering location algorithm was also compared with region growing location method. The location order, time consuming and its robustness against blob noises of the proposed method were discussed. Experiment results show that the proposed algorithm is fit for video sequences whose binary images have big noise blobs and bad spatial connectivity.

关 键 词：减法聚类 目标定位 区域生长 差异积累 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]