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

Abstract. We present and evaluate 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 edge detection. In order to deal with inaccuracy of segmentation results due to distributed and competitive actions performed by autonomous agents, 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, are compared to those of some typical methods for range image segmentation. The comparison results show a good potential of the proposed approach for scene understanding in range images, regarding both segmentation efficiency, and detection accuracy. Key Words:...

• Type: Conference
• Year: 2007
• Where: ACIVS
• Authors: Smaine Mazouzi, Zahia Guessoum, Fabien Michel, Mohamed Batouche
• Keywords: ACIVS 2007, Computer Vision, Edge Regularization, Range Image, Range Image Segmentation