A feature extraction approach for printed Tibetan character based on fractal moments is proposed. After analyzing the existing feature extraction approaches, the image projection approach and the directional line element approach, the fractal moments theory is applied in the proposed approach. The extracted features using the proposed method can describe the local and global properties of the character, and decrease the adverse influence caused by the change of pixel position in the image. The method can overcome high probability of misrecognition of numerous Tibetan characters, and solve the low arithmetic speed problem caused by more feature vector dimensions. Experimental results on 592 categories of printed Tibetan characters show the effectiveness of the proposed method. Moreover, the recognition rate of the proposed approach is about 2.48％ higher than that of any other existing feature extraction approach.