An effective algorithm for segmentation of scene text based on color, maximum gradient difference (MGD),and Markov random field (MRF) model is proposed to overcome the interfere nce of uneven illumination and clutter background to scene text segmentation.Firstly,in view of the compl exity of scene text,the effective texture feature MGD is extracted,and is combined with color feature to make a model for observed image through a probability framework.Secondly,potential function is improved by tak ing advantage of the spatial relationship and attribute difference between neighborhood pixels.Then,an MRF m odel is proposed for the problem of scene text segmentation,and graph cut method is adopted to solve the model quickly under the criterion of minimum energy.Experimental results demonstrate that the proposed method performs well and can achieve better segmentation results compared with other methods,especially in c ase of uneven light and complex background.