A Multi-agent Approach for Range Image Segmentation with Bayesian Edge Regularization

Abstract : We present in this paper a multi-agent approach for range image segmentation. The approach consists in using autonomous agents for the segmentation of a range image in its different planar regions. Agents move on the image and perform local actions on the pixels, allowing robust region extraction and accurate edge detection. In order to improve the segmentation quality, a Bayesian edge regularization is applied to the resulting edges. A new Markov Random Field (MRF) model is introduced to model the edge smoothness, used as a prior in the edge regularization. The experimental results obtained with real images from the ABW database show a good potential of the proposed approach for range image analysis, regarding both segmentation efficiency, and detection accuracy.
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Communication dans un congrès
Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen. ACIVS 2007 - 9th International Conference on Advanced Concepts for Intelligent Vision Systems, Aug 2007, Delft, Netherlands. Springer Berlin / Heidelberg, 4678, pp.449-460, 2007, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/e478585250025l7p/?p=0eb23afec19c48fd9e61b9efe83369c3&pi=0〉. 〈10.1007/978-3-540-74607-2_41〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00394193
Contributeur : Fabien Michel <>
Soumis le : mercredi 10 juin 2009 - 17:56:47
Dernière modification le : vendredi 31 août 2018 - 09:25:56

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Smaine Mazouzi, Zahia Guessoum, Fabien Michel, Mohamed Batouche. A Multi-agent Approach for Range Image Segmentation with Bayesian Edge Regularization. Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen. ACIVS 2007 - 9th International Conference on Advanced Concepts for Intelligent Vision Systems, Aug 2007, Delft, Netherlands. Springer Berlin / Heidelberg, 4678, pp.449-460, 2007, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/e478585250025l7p/?p=0eb23afec19c48fd9e61b9efe83369c3&pi=0〉. 〈10.1007/978-3-540-74607-2_41〉. 〈lirmm-00394193〉

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