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- W1997932664 abstract "In modern traffic surveillance, computer vision methods have often been employed to detect vehicles of interest because of the rich information content contained in an image. Segmentation of moving ve- hicles using image processing and analysis algorithms has been an im- portant research topic in the past decade. However, segmentation re- sults are strongly affected by two issues: moving cast shadows and reflective regions, both of which reduce accuracy and require postpro- cessing to alleviate the degradation. We propose an efficient and highly accurate texture-based method for extracting the boundary of vehicles from the stationary background that is free from the effect of moving cast shadows and reflective regions. The segmentation method utilizes the differences in textural property between the road, vehicle cast shadow, reflection on the vehicle, and the vehicle itself, rather than just the inten- sity differences between them. By further combining the luminance and chrominance properties into an OR map, a number of foreground vehicle masks are constructed through a series of morphological operations, where each mask describes the outline of a moving vehicle. The pro- posed method has been tested on real-world traffic image sequences and achieved an average error rate of 3.44% for 50 tested vehicle im- ages. © 2004 Society of Photo-Optical Instrumentation Engineers." @default.
- W1997932664 created "2016-06-24" @default.
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- W1997932664 date "2004-03-01" @default.
- W1997932664 modified "2023-10-14" @default.
- W1997932664 title "Highly accurate texture-based vehicle segmentation method" @default.
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- W1997932664 doi "https://doi.org/10.1117/1.1645849" @default.
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