Intrinsic scale space for images on surfaces: The geodesic curvature flow (1997) [27 citations — 5 self]
by Ron Kimmel, Lawrence Berkeley, National Laboratory
Graphical Models and Image Processing
http://www.cs.technion.ac.il/~ron/PAPERS/GMIP_kg.ps.gz
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@INPROCEEDINGS{Kimmel97intrinsicscale,author = {Ron Kimmel and Lawrence Berkeley and National Laboratory},
title = {Intrinsic scale space for images on surfaces: The geodesic curvature flow},
booktitle = {Graphical Models and Image Processing},
year = {1997},
pages = {365--372},
publisher = {Springer-Verlag}
}
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Abstract:
A scale space for images painted on surfaces is introduced. Based on the geodesic curvature flow of the iso-gray level contours of an image painted on the given surface, the image is evolved and forms the natural geometric scale space. Its geometrical properties are discussed as well as the intrinsic nature of the proposed flow. I.e. the flow is invariant to the bending of the surface. 1
Citations
| 255 | Image selective smoothing and edge detection by nonlinear diffusion – Alvarez, Lions, et al. - 1992 |
| 229 | Axioms and fundamental equations of image processing – Alvarez, Guichard, et al. - 1993 |
