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Research Journal of Information Technology
  Year: 2012 | Volume: 4 | Issue: 4 | Page No.: 195-203
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Moving Target Detection in Complex Background

Yu-Long Qiao and Xian-Rui Song

Moving target detection is a key problem in many image based applications. For these scenes whose background is complex caused by stochastic motion, it becomes more difficult to well detect the moving targets. This study proposes a center-surround discriminant saliency based detection method using the Stationary Wavelet Transform (SWT) and the generalized Gamma distribution (GΓD). It makes use of the fact that the properties of the moving target and the complex background is different in the stationary wavelet domain and can be described by the GΓD model. The center-surround discriminant saliency which is to measure the difference between the current location and its surround, is determined with the Symmetrized Kullback-Leibler Distance (SKLD) of the GΓD models of the center and surround in the wavelet transform. Then the moving target is detected based on this discriminant saliency. The experimental results demonstrate the effectiveness of the proposed method.
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  •    A Robust Wavelet-Based Watermarking Scheme Using Quantization and Human Visual System Model
  •    Fast Moving Small Target Tracking Based on Local Background Gaussian Mixture Model
  •    A Review on Selected Target Tracking Algorithms
  •    An Improved Algorithm for Image Compression Using Wavelets and Contrast Based Quantization Technique
How to cite this article:

Yu-Long Qiao and Xian-Rui Song, 2012. Moving Target Detection in Complex Background. Research Journal of Information Technology, 4: 195-203.




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