Title :
A Novel Background Extraction and Updating Algorithm for Vehicle Detection and Tracking
Author :
Kong, Jun ; Zheng, Ying ; Lu, Yinghua ; Zhang, Baoxue
Author_Institution :
Northeast Normal Univ., Jilin
Abstract :
This paper proposes a new adaptive background extraction and updating algorithm for vehicle detection and tracking. Gray-level quantification and two attenuation weights are introduced to reduce the impact of environment lighting condition in background extraction method, two discriminant functions are employed to distinguish false moving objects and true moving objects for solving the deadlock problem of background updating. The experimental results show that the proposed method is more robust, accurate and powerful than traditional methods, and is simple to implement and suitable for real-time vehicle detection and tracking.
Keywords :
feature extraction; object detection; traffic engineering computing; adaptive background extraction; background updating algorithm; discriminant function; gray-level quantification; vehicle detection; vehicle tracking; Application software; Clustering algorithms; Color; Gaussian distribution; Object recognition; Optical attenuators; Pixel; Traffic control; Vehicle detection; Video sequences;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.98