A semi-automatic method for extracting thin line structures in images as rooted tree network [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2010. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Additional Creators:
- Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- This paper addresses the problem of semi-automatic extraction of line networks in digital images - e.g., road or hydrographic networks in satellite images, blood vessels in medical images, robust. For that purpose, we improve a generic method derived from morphological and hydrological concepts and consisting in minimum cost path estimation and flow simulation. While this approach fully exploits the local contrast and shape of the network, as well as its arborescent nature, we further incorporate local directional information about the structures in the image. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the target network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given seed with this metric is combined with hydrological operators for overland flow simulation to extract the line network. The algorithm is demonstrated for the extraction of blood vessels in a retina image and of a river network in a satellite image.
- Published through SciTech Connect., 01/01/2010., "la-ur-10-05417", " la-ur-10-5417", International Symposium on Visual Computing ; November 29, 2010 ; Las Vegas, NM., and Soille, Pierre; Dillard, Scott; Brazzini, Jacopo.
- Funding Information:
View MARC record | catkey: 14654446