Comparison between BBO and Genetic Algorithm

“Segmentation” refers to the process of dividing a digital image into multiple segments such as sets of pixels, also known as super pixels. The main objective of segmentation is to simplify and/or change the representation of an image into meaningful image that is more appropriate and easier to analyze. “Image segmentation” is an important aspect of digital image processing. Color images can increase the quality of segmentation, but increase the complexity of the problem. Evolutionary algorithms are well suited to optimizing complex problems such as image segmentation. In this paper two optimization algorithms are explored for image segmentation i.e Genetic algorithm and Biogeography based optimization algorithm. And then compare both these algorithm to show the better optimization and noise free color image segmentation of BBO algorithm as compared to GA. This paper also explores the limitations of GA over BBO.