Polar randomized Hough Transform for lane detection using loose constraints of parallel lines


In this paper, we propose a new methodology for detecting lane markers that exploits the parallel nature of lane bound-aries on the road. First, the input image is pre-processed and filtered to detect lane marker features. Then, using a new technique called Polar Randomized Hough Transform that is introduced in this paper, lines are fitted through the de-tected features and the orientation of each line is evaluated. By finding near parallel lines separated by a constraint speci-fied distance, false signalling caused by artifacts in the image is greatly reduced. The proposed system was tested using a real world driving videos and showed good results despite the presence of neighboring vehicles, shadows, and irregularities on the road surface. Index Terms — Lane detection;Parallel line detection;Polar Randomized Hough Transform 1

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oai:CiteSeerX.psu: time updated on 11/1/2017

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