标题: Real-time Vision-based Multiple Vehicle Detection and Tracking for Nighttime Traffic Surveillance
作者: Chen, Yen-Lin
Wu, Bing-Fei
Fan, Chung-Jui
电控工程研究所
Institute of Electrical and Control Engineering
关键字: Intelligent transportation systems;vehicle detection;vehicle tracking;nighttime surveillance;traffic surveillance
公开日期: 2009
摘要: This study presents an effective system for detecting and tracking moving vehicles in nighttime traffic scene for traffic surveillance. The proposed method identifies vehicles based on detecting and locating vehicle headlights and taillights by using the techniques of image segmentation and pattern analysis. First, to effectively extract bright objects of interest, a fast bright-object segmentation process based on automatic multilevel histogram thresholding is applied on the nighttime road-scene images. This automatic multilevel thresholding approach can provide robustness and adaptability for the detection system to be operated well under various illumination conditions at night. The extracted bright objects are processed by a spatial clustering and tracking procedure by locating and analyzing the spatial and temporal features of vehicle light patterns, and then identifying and classifying the moving cars and motorbikes in the traffic scenes. Experimental results demonstrate that the proposed approach is feasible and effective for vehicle detection and identification in various nighttime environments for traffic surveillance.
URI: http://dx.doi.org/10.1109/ICSMC.2009.5346191
http://hdl.handle.net/11536/134406
ISBN: 978-1-4244-2793-2
ISSN: 1062-922X
DOI: 10.1109/ICSMC.2009.5346191
期刊: 2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9
起始页: 3352
结束页: +
显示于类别:Conferences Paper