This paper addresses the problem of image texture classification. We present a novel texture feature called "characteristic view", which is directly extracted from a sample sub-image corresponding to each texture class. The K-views template method is proposed to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that in an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain classes of features. Different "views" can be obtained for these features from different spatial locations. Experimental results show the effectiveness of the proposed approach compared with other methods.