An efficient ant-based edge detector
Transactions on computational collective intelligence I
Swarm intelligence for medical volume segmentation: the contribution of self-reproduction
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Robust Kinect-based guidance and positioning of a multidirectional robot by Log-ab recognition
Expert Systems with Applications: An International Journal
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In this paper, we describe a segmentation method for brain MR images using an ant colony optimization (ACO) algorithm. This is a relatively new meta-heuristic algorithm and a successful paradigm of all the algorithms which take advantage of the insect’s behavior. It has been applied to solve many optimization problems with good discretion, parallel, robustness and positive feedback. As an advanced optimization algorithm, only recently, researchers began to apply ACO to image processing tasks. Hence, we segment the MR brain image using ant colony optimization algorithm. Compared to traditional meta-heuristic segmentation methods, the proposed method has advantages that it can effectively segment the fine details.