Abstract
Detection of lane and objects is one of the most active areas of research in computer and robotic vision technology for its application in a self-driving car. The autonomous or advanced driver assistance system of a car has to detect the lane and objects from video sequences to make appropriate decisions while moving on the road. Conventionally, two camera-based stereo vision systems may be used to identify the lane and obstacles from video sequences. In this paper, we present a novel technique of lane and obstacle detection by using video/image sequences captured by a stereo vision system based on a single low cost, low-resolution camera. The proposed system utilizes a technique for generating a disparity map in one camera stereo imaging system, which is effectively used to identify the lane and obstacles or other vehicles from the captured real-time video sequences.
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Murmu, N., Nandi, D. (2021). Lane and Obstacle Detection System Based on Single Camera-Based Stereo Vision System. In: Kumar, R., Dohare, R.K., Dubey, H., Singh, V.P. (eds) Applications of Advanced Computing in Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-4862-2_28
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DOI: https://doi.org/10.1007/978-981-33-4862-2_28
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