DocumentCode :
2431676
Title :
Vehicle Stop Detection Algorithm Based on Motion Analysis in Access Control System Application
Author :
Majidi, Ali ; Pourghassem, Hossein ; Nejati, Mansour
Author_Institution :
Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan, Iran
fYear :
2012
fDate :
3-5 Nov. 2012
Firstpage :
690
Lastpage :
694
Abstract :
In This paper, a vehicle stop detection algorithm based on motion analysis in access control system application is proposed. In this algorithm, motion of vehicle in consecutive frames is analyzed and used to determination of frame in which vehicle has been stopped. Motion analysis is carried out based on thresholded difference image calculated for each two sequential frames of a video stream and a verification mask which shows the variations of important edges in these two frames. Then, a decision value is extracted from the refined difference image that determines the vehicle stop frame. In this algorithm, an adaptive thresholding approach based on decision value of previous frames is proposed that compensates the various illumination conditions in day and night. The proposed vehicle stop detection algorithm was evaluated on several videos captured in day and night. The obtained results show efficiency of the proposed algorithm in real and operational conditions.
Keywords :
authorisation; image motion analysis; image sequences; road vehicles; traffic engineering computing; video streaming; access control system application; decision value; image calculation; motion analysis; sequential frames; vehicle stop detection algorithm; video stream; Access control; Algorithm design and analysis; Detection algorithms; Indexes; Licenses; Lighting; Vehicles; Access Control; adaptive thresholding; motion analysis; stop detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4673-2981-1
Type :
conf
DOI :
10.1109/CICN.2012.204
Filename :
6375201
Link To Document :
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