Title :
An Adaptive Shadow Removal Method Based on Weighted Gaussian Model
Author :
Yanjun Zhou ; Xianliang Tong ; Jun Kong ; Ying Zheng
Author_Institution :
Comput. Sch., Northeast Normal Univ., Changchun
Abstract :
The method of the shadow detection and remove which has application value is proposed based on analyzing visual surveillance purposes. The method proposed is essentially based on linear ratio and shadow direction angle threshold to locate the rough shadow regions, considering the relationship of the probability whether it is a shadow pixels and distances which between the shadow pixels and the centroids of the foreground objects. So this paper use the distances to weight the probability regions, and then exactly remove the shadow using the threshold method to locate the exact shadow regions. The experimental result indicates that the algorithm of removing shadow is fast and exact, improves the accuracy of the moving vehicle detection.
Keywords :
Gaussian processes; image motion analysis; object detection; video surveillance; adaptive shadow removal method; moving vehicle detection; probability regions; rough shadow regions; shadow detection; shadow direction angle threshold; shadow pixels; video monitoring system; visual surveillance; weighted Gaussian model; Educational institutions; Flowcharts; Information analysis; Layout; Light sources; Monitoring; Object detection; Pattern recognition; Shape; Video sequences; Distance Weighted; Gaussian Model; Shadow Detection; Shadow Removing;
Conference_Titel :
Business and Information Management, 2008. ISBIM '08. International Seminar on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3560-9
DOI :
10.1109/ISBIM.2008.79