Multiscale matched filter-based lane detection scheme of the constant false alarm rate for driver assistance

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Multiscale matched filter-based lane detection scheme of the constant false alarm rate for driver assistance

Weiwei Zhang

Real-time lane detection is an important element for driver assistance systems in rapidly changing traffic scenarios. In this paper, an embedded lane detection platform combining a high-dynamic-range image sensor is proposed. As for the software development, a multiscale matched filter scheme is successfully used to enhance the local contrast between the lane markings and the background interference for different traffic scenarios. Then, an intelligent constant-false-alarm-rate detector is designed to generate an adaptive threshold for extraction of the lane markings. As for hardware implementation, a field programmable gate array is used for obtaining a high-dynamic-range image, and then matched filters achieve their optimal design based on the coefficient decomposition technology in the form of a fixed point number. Subsequently, through a high-speed serial peripheral interface bus, all pre-processed data are transferred to an ARM processor, which takes charge of extraction of the lane markings and also lane fitting. Experiments and evaluation prove that the proposed system can effectively detect the lane markings for different traffic scenarios in a time of 11.64 ms for each frame.