A Learning-Based Spatial Processing Method for the Detection of Point Targets

  • Zhijun Liu
  • Xubang Shen
  • Hongshi Sang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


In this paper, we present an efficient learning-based method for the detection of point targets in images. In the scheme, the probabilistic visual learning (PVL) technique is used for modeling the appearance of point targets and constructing a saliency measure function. Based on this function and the feature vector extracted at each pixel position and a target saliency map is formed by lexicographically scanning the input image. We treat such saliency map as a spatially filtered result of input image. Experimental results show that the proposed algorithm outperforms other filter-based methods.


Feature Vector Input Image Training Image Point Target Propose Detection Method 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zhijun Liu
    • 1
  • Xubang Shen
    • 1
  • Hongshi Sang
    • 1
  1. 1.Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and TechnologyWuhanChina

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