Nachour, A. and Ouzizi, L. and Aoura, Y. (2018) Fuzzy logic and multi-agent for active contour models. Advances in Intelligent Systems and Computing, 565. pp. 229-237.

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With many techniques and new concepts that use energy minimization in edge-based Active Contour Models, the accurate segmentation is of great interest. However, most existing models are not accurate to capture uncertainty and vagueness appearing around object boundaries. In this work, we developed a model for image segmentation based on an active contour model using fuzzy logic and multi-agent system. We define Fuzzy sets using membership values assigned to local and global features of the active contour points. The parallel agents are employed to define a mapping to crisp sets using the information contained in the fuzzy set. The model is evaluated in several images and compared with other fuzzy ACMs in the literature. The results show that the proposed model can distinguish between noise, background and objects of interest whose boundaries are not necessarily defined by the gradient. In addition, better performance in optimizing runtime is obtained for several tests. © 2018, Springer International Publishing AG.

Item Type: Article
Uncontrolled Keywords: Agents; Computer circuits; Fuzzy sets; Image segmentation; Multi agent systems, Active contour model; Active contours; Energy minimization; Global feature; Membership values; Multi agent; Noise; Object boundaries, Fuzzy logic
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46

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