An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Image Segmentation With Distributed Behavior-Based Agents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
Gradient-based polyhedral segmentation for range images
Pattern Recognition Letters
Range image segmentation based on randomized Hough transform
Pattern Recognition Letters
Image enhancement - An emergent pattern formation approach via decentralised multi-agent systems
Multiagent and Grid Systems - Special Issue on Nature inspired systems for parallel, asynchronous and decentralised environments
Automated segmentation of human brain MR images using a multi-agent approach
Artificial Intelligence in Medicine
Range image segmentation using surface selection criterion
IEEE Transactions on Image Processing
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In this paper we introduce a new distributed approach for image segmentation based on multi-agent systems. Several agents are placed randomly in the image, then each of them starts a region growing around its position. Several agents can be within the same homogeneous region. So, they must exchange information to better labeling pixels reached by these agents. Every labeled pixel is smoothed by replacing its parameters by those of the pixel in the center of the region seed. A set of real range images from the ABW image base was used to evaluate the proposed approach. Experimental results show the potential of the approach to provide an accurate and efficient image segmentation.