An Efficient Image Clustering Technique based on Fuzzy C-means and Cuckoo Search Algorithm

Clustering is a predominant technique used in image segmentation due to its simple, easy and efficient approach. It very important for the analysis, extraction interpretation of images; which makes it multiple applications various fields. In this article, we propose different based on cooperation between an optimization algorithm Cuckoo Search Algorithm (CSA) clustering Fuzzy C-means (FCM). The method goes through two major steps. first step, CSA explores entire search space specified data find optimal centers. Subsequently, these centers are evaluated using new objective function. result step initialize FCM second step. efficiency suggested measured several images selected from BSD300 database compare with other algorithms such as optimized by genetic (FCM-GA) particle swarm (FCM-PSO). experimental results paper show that proposed improves results, analysis best values fitness, MSE, PSNR, CC, RI, GCE, BDE VOI.