Optimization of Fuzzy C Means with Darwinian Particle Swarm Optimization on MRI Image

Image segmentation is one of the most important and most difficult low-level image analysis tasks. Automatic target recognition (ATR) often uses segmentation to separate the desired target from the background. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, and easy to implement. Fuzzy clustering is a main problem which is the subject of dynamic research in several real world applications. However, FCM is sensitive to initialization and is easily trapped in local optima. In this paper, DPSO is used to escape from local optima and to determine the global optima which are calculated on comparing with single swarm and similar set of swarms, operating on the test problem obtained for PSO