A threshold segmentation method based on maximum fuzzy entropy and immune clone selection algorithm is proposed to segment an image with nonuniform illumination.According to the maximum fuzzy entropy principle

the optimal combination of the fuzzy parameters is searched

and the optimal threshold is determined to distinguish the object and background.In order to validate the proposed method

it is tested and compared with genetic algorithm.Experimental results show that the proposed method gives better performance

and can select the threshold automatically and efficiently

and has an advantage of reservation of the main features of the original image.