10 April 2018 Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061505 (2018) https://doi.org/10.1117/12.2302659
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
Abstract
In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user’s defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.
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Orachat Chitsobhuk, Orachat Chitsobhuk, Watjanapong Kasemsiri, Watjanapong Kasemsiri, Sorayut Glomglome, Sorayut Glomglome, Pipatphon Lapamonpinyo, Pipatphon Lapamonpinyo, } "Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061505 (10 April 2018); doi: 10.1117/12.2302659; https://doi.org/10.1117/12.2302659
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