Fuzzy Local Information C-Means Clustering Algorithm

FLICM overcomes limitations of standard FCM while enhancing clustering performance. Its key feature involves a fuzzy local similarity measure incorporating spatial information and gray values, ensuring noise insensitivity and image detail preservation. MATLAB implementation demonstrates FLICM's superior robustness for noisy image segmentation compared to FCM, using neighborhood pixel analysis and adaptive membership functions.