Computer Science ›› 2017, Vol. 44 ›› Issue (5): 294-298.doi: 10.11896/j.issn.1002-137X.2017.05.054

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Foreground Object Detection Based on Improved PBAS

WANG Rong-qi, ZHENG Lin and WANG Biao   

  • Online:2018-11-13 Published:2018-11-13

Abstract: To avoid the problems of PABS (Pixel Based Adaptive Segmenter) such as low accuracy rate of detection,replacement of immobile of slow-moving foreground objects by background ones,and the interference of ghosting,this paper presented a new PBAS which is improved by merging pixel-level information and region-level information.A mea-sure of background dynamics fused with structural information and color information at region level is computed firstly.And then this measure will be used to estimate and control the threshold and learning rate,as well as to detect the foreground object.A spatial neighborhood contrast on pixel-level result is computed in order to solve the interfe-rence of ghosting,and a foreground count machine is introduced to avoid the missing of static object in foreground.The experiment results indicate that the algorithm is insensitive to brightness and velocity of objects,thus the foreground object can be detected effectively,and interference of ghosting can be removed quickly with a high accuracy detection rate 92.7% .

Key words: PBAS algorithm,Target detection,Background subtraction,Background complexity,Elimination of ghosting

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