Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
Directional Segmentation Based on Shear Transform and Shape Features for Road Centerlines Extraction from High Resolution Images
verfasst von : Ruyi Liu, Qiguang Miao, Jianfeng Song, Qing Xue
Erschienen in: Computer Vision
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.