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Region-Based Strategies for Active Contour Models

Rémi Ronfard 1 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : The variational method has been introduced by Kass et al. (1987) in the field of object contour modeling, as an alternative to the more traditional edge detection-edge thinning-edge sorting sequence. Since the method is based on a pre-processing of the image to yield an edge map, it shares the limitations of the edge detectors it uses. In this paper, we propose a modified variational scheme for contour modeling, which uses no edge detection step, but local computations instead only around contour neighborhoods--as well as an "anticipating" strategy that enhances the modeling activity of deformable contour curves. Many of the concepts used were originally introduced to study the local structure of discontinuity, in a theoretical and formal statement by Leclerc & Zucker (1987), but never in a practical situation such as this one. The first pa~ of the paper introduces a region-based energy criterion for active contours, and gives an examination of its implications, as compared to the gradient edge map energy of snakes. Then, a simplified optimization scheme is presented, accounting for internal and external energy in separate steps. This leads to a complete treatment, which is described in the last sections of the paper (4 and 5). The optimization technique used here is mostly heuristic, and is thus presented without a formal proof, but is believed to fill a gap between snakes and other useful image representations, such as split-and-merge regions or mixed line-labels image fields.
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Submitted on : Wednesday, December 8, 2010 - 3:07:24 PM
Last modification on : Friday, February 4, 2022 - 3:23:25 AM


  • HAL Id : inria-00544609, version 1



Rémi Ronfard. Region-Based Strategies for Active Contour Models. International Journal of Computer Vision, 1994, 13 (2), pp.229-251. ⟨inria-00544609⟩



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