Thin Nets and Crest Lines: Application to Satellite Data and Medical Images

摘要

In this paper, we describe a new approach for extractingthin netsin gray-level images. The key point of our approach is to model thin nets as crest lines of the image surface. Crest lines are lines where the magnitude maximum curvature is a local maximum in the corresponding principal direction. We define these lines using first, second, and third derivatives of the image. The image derivatives are computed using recursive filters approximating the Gaussian filter and its derivatives. Using an adaptive scale factor, we apply this approach to the extraction of roads in satellite data, blood vessels in medical images, and actual crest lines in depth maps of human faces.