Toward application of extremal optimization algorithm in image segmentation

Extremal optimization (EO) algorithm is a kind of evolutionary optimization method which has been applied successfully in different fields. In this paper a new framework is proposed for applying extremal optimization in image segmentation. over segmented images are the initial to EO which works on two levels: segments and pixels. A new energy function is defined for segments and the energy function in markov random fields (MRF) is used for pixels. Applying EO in segment level accelerates the speed of the algorithm. The results show that by defining a suitable energy function, EO can be succeed in merging similar segments and provide a visually good segmentation.