Modified thermal exchange optimization based multilevel thresholding for color image segmentation

This paper proposes a multi-threshold image segmentation method based on modified thermal exchange optimization (TEO). Although it is efficient and gives excellent result in the case of bi-level thresholding, but it takes a lot of computation when the number of threshold increases. To overcome this problem, the TEO algorithm is applied in this search area for searching the optimal thresholds. The Levy flight algorithm is employed to modify the original TEO and balance the exploration and exploitation of TEO. Experiments are conducted between six state-of-the-art metaheuristic algorithms and the proposed one. The benchmark functions, color nature images and stellite images are used in the experiment to test the performance of the algorithms involved. Qualitative experimental results show that the proposed segmentation approach has fewer iterations and higher segmentation accuracy.