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›› 2010, Vol. 27 ›› Issue (3): 370-375.DOI: 10.7523/j.issn.2095-6134.2010.3.010

• Research Articles • Previous Articles     Next Articles

An automatic object detection method based on covariance matrix

NING Zhong-Lei1,2,3, WANG Hong-Qi1,2, ZHANG Zheng1,2,3   

  1. 1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    2. Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China;
    3. Graduate University, Chinese Academy of Sciences, Beijing 100049, China
  • Received:2009-10-10 Revised:2010-01-18 Online:2010-05-15

Abstract:

In order to apply the covariance matrix algorithm to automatic target detection we present feature similarity and covariance matrix similarity. Feature similarity is the similarity of the target feature. Covariance matrix similarity integrates all the feature similarities. In addition, because features are different in validity and importance, we raise minimized feature similarity. Minimized feature similarity can be used to get rid of basically ineffective features. Experiments show that with this method one can effectively apply the covariance matrix algorithm to automatic target detection with high detection rate and low false alarm rate.

Key words: covariance matrix, automatic target detection, feature fusion

CLC Number: