This document discusses a novel image segmentation and feature extraction method that combines Ant Colony Optimization (ACO) and fuzzy logic to address challenges of clustering in image analysis. The proposed approach enhances the identification of image structures by using fuzzy inference rules alongside ACO, thus reducing misclassifications in overlapping regions. Experimental results demonstrate improved performance in extracting features from both textured and non-textured images compared to existing methods.