Improved surendra background updating algorithm for moving vehicle detection

Moving object detection plays an important role in intelligent transportation system. Combined with dynamic segmentation threshold and the counter, this paper proposes an improved Surendra algorithm based on background subtraction method. Image sequence is firstly preprocessed by median filtering, followed by background model updating on basis of dynamic background subtraction. Counter is incorporated to offset the effects of stagnation of moving vehicles and camera vibration. Mathematical morphology operations including connectivity components analysis and iterative dilating are applied to remove noises and fill holes. Experimental results show that the proposed method is efficient and can perform in real time.

[1]  Zhuo Zhang,et al.  Motion Target Detection of Birds Based on Adaptive Background Update Mechanism , 2013 .

[2]  Synh Viet-Uyen Ha,et al.  Occlusion vehicle detection algorithm in crowded scene for Traffic Surveillance System , 2017, 2017 International Conference on System Science and Engineering (ICSSE).

[3]  Song Zheng,et al.  An Improved Moving Object Detection Algorithm Based on Frame Difference and Edge Detection , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).

[4]  Li Qin,et al.  Detection method for vehicles in tunnels based on surveillance images , 2017, 2017 4th International Conference on Transportation Information and Safety (ICTIS).

[5]  P. G. Michalopoulos,et al.  Vehicle detection video through image processing: the Autoscope system , 1991 .

[6]  Zhang Ta Modeling and Analysis of Vehicle Flow Detection Based on Video , 2014 .

[7]  Tao Zhang,et al.  A Novel Method on Moving-Objects Detection Based on Background Subtraction and Three Frames Differencing , 2010, 2010 International Conference on Measuring Technology and Mechatronics Automation.

[8]  Synh Viet-Uyen Ha,et al.  Occlusion vehicle detection algorithm in crowded scene for Traffic Surveillance System , 2017 .

[9]  Baocai Yin,et al.  Vehicle Detection through Traffic Video in Congested Traffic Flow , 2016, 2016 6th International Conference on Digital Home (ICDH).

[10]  Paola Mello,et al.  Image analysis and rule-based reasoning for a traffic monitoring system , 2000, IEEE Trans. Intell. Transp. Syst..