Because of the existence of transition zones in a cold rolling strip surface defect image, gray information and spatial structure information should be combined to segment images to obtain better image results.Therefore, the excess entropy of information entropy and fuzzy set theory were researched.As the excess entropy could be used to measure spatial structure of an image and the characteristic of image gray transition zone could be described well by the fuzzy set, an image threshold segmentation algorithm based on maximal fuzzy excess entropy was proposed.The fuzzy excess entropy was built by the combination of excess entropy and fuzzy set theory and the threshold was determined by the best membership function parameter combination according to the maximal fuzzy excess entropy value. Then, the image was segmented by using the threshold. Finally, the algorithm was compared with Ostu and 1D maximal fuzzy entropy segmentation algorithms. The experiment indicates that the proposed algorithm can extract the defect from a background exactly and can constrain the over-segmentation effectively. The quantificational evaluation of segmented image was performed by the wrong segmentation rate and effective information rate, and the results show that the effective information rate of the algorithm is higher than 82.7%, which is the maximal one among three methods.Meanwhile the wrong segmentation rate is below 2.1%.