Image segmentation with a fuzzy clustering algorithm based on Ant-Tree

This paper presents a fuzzy clustering approach for image segmentation based on Ant-Tree algorithm, which is inspired from the ants’ self-assembling behavior. Three features including the gray value, gradient and neighborhood of pixels are extracted for clustering. A three-level tree model is proposed to make the clustering structure more adaptive for image segmentation. Center approximation is employed to optimize the fuzzy clustering process when building the tree structure. Besides, we present a new initialization method by making use of the histogram of the image. Experiments and comparisons show the effectiveness and the efficiency of the proposed approach.