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An Adaptative Multi-agent System Approach for Image Segmentation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 51 - Number 12 |
| Year of Publication: 2012 |
| Authors: Redjimi Mohammed, Amri Said |
10.5120/8095-1676
|
Redjimi Mohammed, Amri Said . An Adaptative Multi-agent System Approach for Image Segmentation. International Journal of Computer Applications. 51, 12 ( August 2012), 21-26. DOI=10.5120/8095-1676
Abstract
This article presents a multi-agent approach for the segmentation of images. A multi-agent system (MAS) is a distributed system consisting of a set of agents that interact with themselves in an environment they are able to perceive and on which they can act. The proposed solution consists in cutting the space of the image to treat it in a set of sub-spaces (partitions of the image) in which several agents are created to detect the outlines of objects then to follow them (these agents are called detector – followers agents). These agents adapt a very efficient algorithm of detection and follow the outline according to the characteristics of the region that they evolve in. The information so collected is transmitted to levels of supervision agents (agents partitions) which take care they with collecting the information emitted by the agents detector - followers, to update tables containing the parameters of segmentation and to elaborate global strategies of management of the agents detector - followers (creation, destruction, setting in a stand-by mode or initialization of agents detector-followers) . At the highest level of this agent's hierarchy, we find the supervisor agent of this whole system. An implementation of this approach by the use of Madkit system allowed us to observe a gain in performances and in precision very important due to parallel, concurrent and cooperating execution of tasks.
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