A MULTI-AGENT APPROACH FOR EDGE DETECTION USING A GENETIC ALGORITHM FOR PARAMETERS’ SPACE EXPLORATION - LABED, SAID; DRAA, AMER; CHIKHI, SALIM (Courrier du Savoir; مجلد 14 (2012): Courrier du Savoir, 2014)
In  this  paper,  an  agent  based  approach  for  edge  detection  is  presented.  It  uses  the  blackboard  system  as  a  means  of communication between agents. A population of agents is deployed on a two-dimensional representation of an image. Every agent is able to decide whether the pixel on which it is situated belongs or does not belong to the homogeneous region looked for,  and  thus  to  exhibit  a  reactive  behaviour:  breeding  and  labelling,  or  diffusion,  allowing  the  emergence  of  a  complex phenomenon at the global level. This phenomenon is the segmentation of the image. The behaviour of agents is inspired from the natural diffusion phenomenon. The approach has been implemented with the Netlogo platform which  is a very powerful agent based simulator, and since the parameters space is very huge, a genetic algorithm has been used to lessen the complexity of the problem.