A Template Matching and Ellipse Modeling Approach to Detecting Lane Markers

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• 作者：Amol Borkar ; Monson Hayes ; Mark T. Smith
• 关键词：Lane Detection and Lane Keeping ; Template Matching ; Driver Assistance Systems ; Advanced Vehicle Safety Systems
• 刊名：Lecture Notes in Computer Science
• 出版年：2010
• 出版时间：2010
• 年：2010
• 卷：6475
• 期：1
• 页码：179-190
• 全文大小：530.5 KB

文摘

Lane detection is an important element of most driver assistance applications. A new lane detection technique that is able to withstand some of the common issues like illumination changes, surface irregularities, scattered shadows, and presence of neighboring vehicles is presented in this paper. At first, inverse perspective mapping and color space conversion is performed on the input image. Then, the images are cross-correlated with a collection of predefined templates to find candidate lane regions. These regions then undergo connected components analysis, morphological operations, and elliptical projections to approximate positions of the lane markers. The implementation of the Kalman filter enables tracking lane markers on curved roads while RANSAC helps improve estimates by eliminating outliers. Finally, a new method for calculating errors between the detected lane markers and ground truth is presented. The developed system showed good performance when tested with real-world driving videos containing variations in illumination, road surface, and traffic conditions.