In image analysis, it is widely assumed that the number of parameters of deformable models is strongly dependent of the image resolution. For highly deformable models, which adapts their topology to their geometrical changes, all explicit and implicit methods have a number of parameters and a time complexity at least linear with the number of pixels or voxels of the component to extract. We show here that a preprocessing of the image can emphasize interesting parts of the image while diminishing the apparent significance of noisy or homogoneous image regions. This zooming effect focuses model parameters and computations on the interesting part of the images. As a consequence, about five time less vertices in 2D and ten times less vertices in 3D are sufficient to extract image components with the same accuracy. Running times are also sped up by a factor ten in 3D.
Lachaud05b , Lachaud04a , Lachaud03d , Taton02b
J.O. Lachaud and B. Taton. Deformable Model with a Complexity Independent from Image Resolution. Computer Vision and Image Understanding, 99(3): 453475. 2005.
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J.O. Lachaud and B. Taton. Resolution Independent Deformable Model. In Proc. 17th int. Conf. on Pattern Recognition (ICPR'2004), Cambridge, United Kingdom, 2326 August, volume II, pages 237240, 2004. IEEE Computer Society Press.
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J.O. Lachaud and B. Taton, Deformable Model with Adaptive Mesh and Automated Topology Changes. In M. Rioux, P. Boulanger and G. Godin, editors, Proc. 4th int. Conf. 3D Digital Imaging and Modeling (3DIM'2003), Banff, Alberta, Canada, 2003. IEEE Computer Society Press.
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B. Taton and J.O. Lachaud. Deformable Model with nonEuclidean Metrics. In A. Heyden, G. Sparr, M. Nielsen, and P. Johansen, editors, Proc. 7th European Conference on Computer Vision (ECCV'2002), Copenhagen, Denmark, volume 2352 (part III) of LNCS, pages 438453, 2002. Springer, Berlin.
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