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Published in:
2015 | OriginalPaper | Chapter
Directional Segmentation Based on Shear Transform and Shape Features for Road Centerlines Extraction from High Resolution Images
Authors : Ruyi Liu, Qiguang Miao, Jianfeng Song, Qing Xue
Published in: Computer Vision
Publisher: Springer Berlin Heidelberg
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Accurate extraction of road networks from high resolution remote sensing images is a problem not satisfactorily solved by existing approaches, especially when the color of road is close to that of background. This paper studies a new road networks extraction from remote sensing images based on the shear transform, the directional segmentation, shape features and a skeletonization algorithm. The proposed method includes the following steps. Firstly, we combine shear transform with directional segmentation to get road regions. Secondly, road shape features filtering are used to extract reliable road segments. Finally, the road centerlines are extracted by a skeletonization algorithm. Road networks are then generated by post-processing. Experimental results show that this method is efficient in road centerlines extraction from remote sensing images.