Image segmentation using firefly algorithm

Abstract

Image segmentation is an important step in the domain of image processing in which we segment the image into several parts which carry certain type of information for the user. Image segmentation is very difficult step in the processing of the image which aims at extracting the information from image. Clustering is used to segment the image. Clustering algorithms are part of data mining algorithm that groups the data into various number of given clusters. All the data points in one cluster have similar properties based on which they are clustered i.e. each cluster has minimum difference between its points and maximum difference from other cluster data points. The proposed algorithm uses k-mean algorithm and firefly to cluster image pixels into k cluster for segmentation. Since k-mean clustering algorithm is gets trapped in local optima it is optimized using firefly algorithm. Swarm intelligence based algorithms forms the basis of the firefly algorithm which has several application and used to solve optimization problems. Firefly algorithm has been applied in many research and optimization areas. Firefly algorithm and its hybridized version have been used to solve various problems successfully. To apply firefly algorithm to wide areas of problem the firefly algorithm must be modified or integrated with other algorithms. Presently metaheuristic nature of algorithm plays an important role and current optimization algorithm include this nature and are very efficient in solving NP-hard problems.