A semi-automatic method for extracting thin line structures in images as rooted tree network
- Los Alamos National Laboratory
- EC - JRC
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.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1027486
- Report Number(s):
- LA-UR-10-05417; LA-UR-10-5417; TRN: US201121%%385
- Resource Relation:
- Conference: International Symposium on Visual Computing ; November 29, 2010 ; Las Vegas, NM
- Country of Publication:
- United States
- Language:
- English
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