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A ViBe Based Moving Targets Edge Detection Algorithm and Its Parallel Implementation

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Abstract

In order to improve the computational speed and detection accuracy of the ViBe algorithm in foreground edge detection, an improved algorithm based on ViBe moving objects edge detection is proposed in this study by using the partial neighborhood model H(x, y) of a pixel at the point (x, y) to find the absolute difference between H(x, y) and the pixel’s original background model M(x, y) to determine if the pixel is moving. According to the nature of the algorithm, a method based on offset thread block coordinates to optimize thread divergence is proposed from the perspective of calculation level of kernel function and a CUDA (computing unified device architecture) based method is propsed to optimize the stream transmission between CPU and GPU in order to the run time efficiency of the new algorithm. The experimental results indicated the improved algorithm implements ghost elimination, avoids large-area irrelevant background edges and achieves better efficiency and accuracy.

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Authors and Affiliations

  1. School of Software, Xinjiang University, Ürümqi, 830008, China

    Han Zhang, Yurong Qian, Yuefei Wang, Renhe Chen & Chenwei Tian

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  1. Han Zhang
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  2. Yurong Qian
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  3. Yuefei Wang
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  4. Renhe Chen
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  5. Chenwei Tian
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Correspondence to Han Zhang.

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Funded by the National Natural Science Foundation of China (61562086, 61462079), Xinjiang Uygur Autonomous Region Innovation Team XJEDU2017T002.

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Zhang, H., Qian, Y., Wang, Y. et al. A ViBe Based Moving Targets Edge Detection Algorithm and Its Parallel Implementation. Int J Parallel Prog 48, 890–908 (2020). https://doi.org/10.1007/s10766-019-00628-z

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  • DOI: https://doi.org/10.1007/s10766-019-00628-z

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