An Algorithm for Swarm-based Color Image Segmentation

Segmentation of nontrivial color images is one of the most difficult tasks in digital image processing. This paper presents a novel color image segmentation algorithm, which uses a biologically inspired paradigm known as swarm intelligence, to segment images based on color similarity. The swarm algorithm employed uses image pixel data and a corresponding segment map to form a context in which stigmergy can occur. The emergent property of the algorithm is that connected segments of similar pixels are found and may later be referenced. We demonstrate the algorithm by applying it to the task of segmenting digital images of butterflies for the purpose of automatic classification.