A Hybrid Image Segmentation Method Using Firefly And Artificial Bee Colony Algorithms For Color Images

Abstract

In Image segmentation, optimization problems have been efficiently solved by two notable swarm intelligence algorithms, Firefly Algorithm (FA) and Artificial Bee Colony (ABC). The proposed methodology presents a hybrid approach for image segmentation by integrating both the Firefly and Artificial Bee Colony (HFAABC) Algorithm is proposed for solving optimization problems. This proposed algorithm, FA investigates the search space globally to locate favorable regions of convergence and ABC is employed to perform local search. To segment the color images using by Fuzzy C-Means (FCM) method. The extracted objects are optimally selected by means of Hybrid Firefly and artificial bee colony (HFAABC). The implementation result shows the efficiency of proposed segmentation method in segmenting the images. The experimental results demonstrate the effectiveness of the proposed HFAABC algorithm and showed that it overtakes other algorithms in terms of performance measures, such as Peak Signal-to-Noise Ratio (PSNR) and Accuracy.