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Caste Shadow Removal in Vehicle Detection using Mixture of Gaussian for Traffic Surveillance System

Author(s): Vanraj Dangar | Amit Thakkar

Journal: International Journal of Advanced Research in Computer Science
ISSN 0976-5697

Volume: 04;
Issue: 04;
Start page: 374;
Date: 2013;
Original page

Keywords: Background | subtraction | Gaussian | Mixture | Model | JRF | model | Caste | Shadow | Thresolding

Observing moving objects in a site and removal of caste shadow is a critical task in computer vision. This paper presents an algorithm fordetection and caste removal of vehicles in real-time video which is streamed by a camera with fixed position. Processing of the video is done in two steps: Vehicle Detection and Caste shadow removal. Identifying moving object is done by classification of pixels into either foreground (object) or background. Vehicle detection is achieved by the use of Background subtraction. Many existing scheme of background removal presenting different background models like Mixture of Gaussian (MoG) and Joint Random Field (JRF) will be discussed. A simple approach to remove caste shadow area from the detected foreground objects will also be discussed.
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