Abstract
Vision-based road detection is a challenging task due to surrounding scenes and types of roads. This paper describes an efficient and effective algorithm for general road segmentation and tracking. The major contributions of this paper are three aspects: 1) an optimised voter selection strategy-based modified voting process for vanishing point detection; 2) use of Kalman filter to avoid false detection of vanishing point and reduction in computational complexity of final road segmentation; 3) the algorithm is evaluated against different road types with varying surrounding scenes. The method has been implemented and tested with 10,000 video frames of Indian road scenes. Experimental results demonstrate that the algorithm achieves better efficiency compared to some of the texture-based vanishing point detection algorithms and successfully segments drivable road regions from varying Indian road scenes.
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