Merged Biogeography-Based Optimization Algorithm for Color Image Segmentation

Image segmentation is an important step in image processing. Segmentation based on threshold is a common method. Searching the suitable threshold vector is essentially an optimization problem, especially for color image which have higher dimensions and complexity. This paper proposes a merged Biogeography-Based Optimization algorithm (MBBO) for color image segmentation based on threshold. We merge a mutation operation into the migration operator of BBO to enhance the global search ability. Then we merge a chemotaxis operation into the mutation operator of BBO to enhance the local search ability. A greedy selection method is also used to further improve the performance and reduce computation complexity. Experimental results show that MBBO obtains better optimization performance, stronger stability and faster running speed compared with other existing algorithms.