An Agent-Based Approach for Range Image Segmentation

Smaine Mazouzi 1 Zahia Guessoum 2 Fabien Michel 3 Mohamed Batouche 4
1 CRESTIC - Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804
2 SMA - Systèmes Multi-Agents
LIP6 - Laboratoire d'Informatique de Paris 6
3 SMILE - Système Multi-agent, Interaction, Langage, Evolution
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
4 LIRE laboratory, Constantine
Abstract : In this paper an agent-based segmentation approach is presented and evaluated. The approach consists in using a high number of autonomous agents for the segmentation of a range image in its different planar regions. The moving agents perform cooperative and competitive actions on the image pixels allowing a robust extraction of regions and an accurate edge detection. An artificial potential field, created around pixels of interest, allows the agents to be gathered around edges and noise regions. The results obtained with real images are compared to those of some typical methods for range image segmentation. The comparison results show the potential of the proposed approach for scene understanding in range images regarding both segmentation efficiency, and detection accuracy.
Keywords : Multi-agent systems Image segmentation Range image Artificial potential field
Type de document :
Chapitre d'ouvrage
Nadeem Jamali, Paul Scerri and Toshiharu Sugawara. Massively Multi-Agent Technology, 5043, Springer, pp.146-161, 2008, Lecture Notes in Computer Science, 〈10.1007/978-3-540-85449-4_11〉. 〈http://www.springerlink.com/content/r784304745074728/〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00520965
Contributeur : Fabien Michel <>
Soumis le : vendredi 24 septembre 2010 - 15:52:30
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

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UPMC | LIP6 | SMILE | LIRMM | MIPS | URCA | UNIV-MONTPELLIER | CRESTIC

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Smaine Mazouzi, Zahia Guessoum, Fabien Michel, Mohamed Batouche. An Agent-Based Approach for Range Image Segmentation. Nadeem Jamali, Paul Scerri and Toshiharu Sugawara. Massively Multi-Agent Technology, 5043, Springer, pp.146-161, 2008, Lecture Notes in Computer Science, 〈10.1007/978-3-540-85449-4_11〉. 〈http://www.springerlink.com/content/r784304745074728/〉. 〈lirmm-00520965〉

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