An Improved Moving Object Detection Algorithm Based on Colour Separation

An improved background subtraction algorithm based on color separation method is improved to solve the problem of high rate of missing detection of moving targets in video surveillance. First, the algorithm implements the background subtraction of the current frame and the background frame for pixel...

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Vydáno v:Applied Mechanics and Materials Ročník 556-562; s. 3074 - 3077
Hlavní autoři: Zhang, Wei, Xu, Wei Hong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Zurich Trans Tech Publications Ltd 01.05.2014
Témata:
Background Subtraction
Color Separation
Target Detection
Moving Target
ISBN:3038351156, 9783038351153
ISSN:1660-9336, 1662-7482, 1662-7482
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Abstract An improved background subtraction algorithm based on color separation method is improved to solve the problem of high rate of missing detection of moving targets in video surveillance. First, the algorithm implements the background subtraction of the current frame and the background frame for pixel blocks in independent RGB channels. Then the three foreground targets after denoising extracted respectively from three channels are combined by or operation to get a complete moving target. And then this algorithm removes the shadow in color model. After that the background frame from each channel is updated individually by recursive algorithm. The algorithm adopts a nonlinear way to change the learning factor for background updating. The experiments show that this improved algorithm can extract effectively foreground targets which are similar to the background’s grey level, with better accuracy and robustness.
AbstractList An improved background subtraction algorithm based on color separation method is improved to solve the problem of high rate of missing detection of moving targets in video surveillance. First, the algorithm implements the background subtraction of the current frame and the background frame for pixel blocks in independent RGB channels. Then the three foreground targets after denoising extracted respectively from three channels are combined by or operation to get a complete moving target. And then this algorithm removes the shadow in color model. After that the background frame from each channel is updated individually by recursive algorithm. The algorithm adopts a nonlinear way to change the learning factor for background updating. The experiments show that this improved algorithm can extract effectively foreground targets which are similar to the background’s grey level, with better accuracy and robustness.
Author Zhang, Wei
Xu, Wei Hong
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Cites_doi 10.1109/CVPR.1999.784637
10.1109/34.598236
10.2174/2213275910801030219
10.1117/1.3542038
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Keywords Background Subtraction
Color Separation
Target Detection
Moving Target
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Notes Selected, peer reviewed papers from the 2014 International Conference on Mechatronics Engineering and Computing Technology (ICMECT 2014), April 9-10, 2014, Shanghai, China
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