Abstract
In this paper, we propose an adaptive local thresholding method for roads segmentation based on the normalization of HSV and Lab color models. The color normalization improves the road’s intensity to be better segmented by the adaptive local thresholding method. In the experiments, we implement tests with the Massachusetts roads dataset with aerial images. Segmentation results are assessed by the Dice and the Jaccard similarities. We also compare segmentation results of the proposed method to the one of the Otsu method to prove its own effectiveness.
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Thanh, L.T., Thanh, D.N.H. (2020). An Adaptive Local Thresholding Roads Segmentation Method for Satellite Aerial Images with Normalized HSV and Lab Color Models. In: Solanki, V., Hoang, M., Lu, Z., Pattnaik, P. (eds) Intelligent Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1125. Springer, Singapore. https://doi.org/10.1007/978-981-15-2780-7_92
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DOI: https://doi.org/10.1007/978-981-15-2780-7_92
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