文章基本信息

标题：SVM BASED ROAD SURFACE DETECTION TO IMPROVE PERFORMANCE OF ABS
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作者：T.ANBALAGAN ; C.GOWRISHANKAR ; Dr.A.SHANMUGAM 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：51
期号：2
出版社：Journal of Theoretical and Applied
摘要：Advance information about the road surface a vehicle is going to encounter can improve the performance of Antilock Braking System (ABS). For e.g. the initial slip cycles caused by the ABS could be avoided, if it is already known that the vehicle is on a surface having a low coefficient of friction (�). In this paper, an algorithm is developed that detects different road surfaces using streaming video acquired from a camera mounted on the hood of the vehicle. The road surfaces detected here are asphalt road, cement road, sandy road, rough asphalt road (asphalt road which is deteriorating), grassy road and rough road. The value of coefficient of friction (�) is also given out with the detected surfaces to obtain additional information about the road surfaces. Split � (a road having different � conditions on the left and right side of the vehicle) and � jump (different � conditions on the front and rear of the vehicle) are also pre detected. One method was not sufficient to achieve the goals of this algorithm. Here several simple techniques like the Canny edge algorithm, intensity histogram, contours, Hough transform and image segmentation were employed and compared with the Support Vector Machine (SVM). To prevent misdetections, the road surface detection during high motion blur is prohibited.
关键词：Computer vision; Vehicle dynamics; Vehicle safety system; Signal processing; Automotive systems; Electronics in industry and transport