This paper propose an off-line Thai character recognition system for an unconstrain writing. This system combines both global feature, that represents character shape, and local feature, that represents the symbolic structure, to solve the similarity and variety problems of Thai characters. The pixel distribution is applied, as the global feature, to classify the image into 20 groups of similar characters. The modified structure features extraction is used to extract character structure. Then, all features, global and local, are used to classify the character within each group. The proposed method yields the recognition rate at 87.32 percents.