A Multi-agent Approach for the Edge Detection in Image Processings

Several multi-agent approaches have been proposed to improve image processing. They use several image processing algorithms simultaneously. However, these approaches do not deal with the inherent problems encountered for the extraction from an image of primitive information like edges or regions. This implies that agents use macro results provided by image processing algorithms. Agents use macro results provided by image processing algorithms. Then, the results do not take advantage of all the interesting characteristics, such as environmental adaptability and emergent behavior capability, of agent-based systems: the combinative explosion of the possible solutions offered by this kind of systems, is highly reduced. In this paper, we propose a multi-agent system based on instinctual [5] reactive agents, which are able to detect edges. Agents locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using a Kirsch derivative and a Gradient Vector Flow. Edges detection emerges from agents interaction. Problems of partial or hidden contours are solved with the cooperation between the different agents. In the scope of this paper, we illustrate our approach through an example that shows how it can be used to detect lungs on 2D images coming from a scan device.