Volume 42 Issue 12
Jan.  2014
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Wang Luping, Zhang Luping, Han Jiantao. Detecting algorithm of moving target in dynamic background based on gray-weighted kernel function[J]. Infrared and Laser Engineering, 2013, 42(12): 3453-3457.
Citation: Wang Luping, Zhang Luping, Han Jiantao. Detecting algorithm of moving target in dynamic background based on gray-weighted kernel function[J]. Infrared and Laser Engineering, 2013, 42(12): 3453-3457.

Detecting algorithm of moving target in dynamic background based on gray-weighted kernel function

  • Received Date: 2013-04-16
  • Rev Recd Date: 2013-05-12
  • Publish Date: 2013-12-25
  • A new detecting algorithm based on gray-weighted kernel function was proposed to solve the proplem of low running rate and high false alarm within the moving target detection(MTD) in dynamic series of image. This algorithm firstly realized image sequence registration by using the biggest gradient block, then divided the image into 3232 sub-images. It could calculate gray-weighted kernel function for every sub-image and detect changing of gray-weighted kernel function by using Bhattacharyya coefficient as similarity principle for every sub-image. The moving target could be detected in sub-image which gray-weighted kernel function has changed. The testing result shows that the algorithm with batter performance of real-time and robustness can detect the moving target in real-time and suppress the influence due to image registration error and gray fluctuation effectively.
  • [1] Lipton A, Fujiyoshi H, Patil R S. Moving target detection and classification from real-time video[R]. In Proceedings of IEEE WACV98, 1998, 778-783.
    [2]
    [3]
    [4] Barron J, Fleet D, Beauchemin S. Performance of optical flow techniques[J]. International Journal of Computer Vision, 1994, 12(1): 43-77.
    [5]
    [6] Mikolajczyk K, Schmid C. Indexing based on scale invariant interest points[C]//Proceedings of International Conference on Computer Vision, 2001: 525-531.
    [7] Yosi K, Amir A. Fast gradient methods based on global motion estimation for video compression[J]. IEEE Trans on Circuits System Video Technol, 2003, 13(4): 300-309.
    [8]
    [9] Collins R A. System for video surveillance and monitoring:VSAM final report.Carnegie mellon university technical report[R]. CMU-RI-TR-00-1 2, 2000.
    [10]
    [11]
    [12] Luo Jun. Application and implementation of moving estimate in image stabilation and matching[D]. Changsha: National University of Defense Technology, 2007.
    [13] Li Jicheng. Research of infrared small target detecting technology in clutter background[D]. Changsha: National University of Defense Technology, 1998. 
    [14]
    [15] Li Long, Li Junshan, Ye Xia. Airborne infrared target tracking based on Mean Shift[J]. Infrared and Laser Engineering, 2007, 36(2): 229-230. (in Chinese)
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Detecting algorithm of moving target in dynamic background based on gray-weighted kernel function

  • 1. School of Electronics Science and Engineering,National University of Defense Technology,Changsha 410073,China

Abstract: A new detecting algorithm based on gray-weighted kernel function was proposed to solve the proplem of low running rate and high false alarm within the moving target detection(MTD) in dynamic series of image. This algorithm firstly realized image sequence registration by using the biggest gradient block, then divided the image into 3232 sub-images. It could calculate gray-weighted kernel function for every sub-image and detect changing of gray-weighted kernel function by using Bhattacharyya coefficient as similarity principle for every sub-image. The moving target could be detected in sub-image which gray-weighted kernel function has changed. The testing result shows that the algorithm with batter performance of real-time and robustness can detect the moving target in real-time and suppress the influence due to image registration error and gray fluctuation effectively.

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