Abstract
The geographic information system industry would benefit from flexible automated systems capable of extracting linear structures from satellite imagery. Quadratic snakes allow global interactions between points along a contour, and are well suited to segmentation of linear structures such as roads. However, a single quadratic snake is unable to extract disconnected road networks and enclosed regions. We propose to use a family of cooperating snakes, which are able to split, merge, and disappear as necessary. We also propose a preprocessing method based on oriented filtering, thresholding, Canny edge detection, and Gradient Vector Flow (GVF) energy. We evaluate the performance of the method in terms of precision and recall in comparison to ground truth data. The family of cooperating snakes consistently outperforms a single snake in a variety of road extraction tasks, and our method for obtaining the GVF is more suitable for road extraction tasks than standard methods.
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© 2007 Springer-Verlag Berlin Heidelberg
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Marikhu, R., Dailey, M.N., Makhanov, S., Honda, K. (2007). A Family of Quadratic Snakes for Road Extraction. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_7
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DOI: https://doi.org/10.1007/978-3-540-76386-4_7
Publisher Name: Springer, Berlin, Heidelberg
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