Abstract
We propose a new method for robust road detection under noise and illumination varying conditions. Original input image is first divided into smooth and detailed component through structure-texture decomposition, where we verify the texture image is robust to various complicated road conditions. The texture image is then be used to compute each pixel’s dominant orientation through Gabor wavelet analysis, followed by generating the vanishing point via grouping voters, which has an orientation confidence larger than a fixed threshold, in corresponding voting region through soft voting. Finally the road borders are constructed by feature inconsistency maximization criterion. Experiments on various road, weather, noise and lighting conditions are justified the accuracy and robust of our method. Furthermore, we analyze the applicability of texture based vanishing point method and conclude the main factors that degenerate the performance of this class method.
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Luo, W., Chang, H., Yang, J. (2013). Noise and Illumination Invariant Road Detection Based on Vanishing Point. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_9
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DOI: https://doi.org/10.1007/978-3-642-36669-7_9
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