A family of quadratic snakes for road extraction

Authors:
Ramesh Marikhu;Matthew N. Dailey;Stanislav Makhanov;Kiyoshi Honda
Affiliations:
Information and Communication Technologies, Asian Institute of Technology;Computer Science and Information Management, Asian Institute of Technology;Sirindhorn International Institute of Technology, Thammasat University;Remote Sensing and GIS, Asian Institute of Technology
Venue:
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Year:
2007

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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.