We present a new texture analysis method, namely a texture feature coding method (TFCM), for classification of the Brodatz's natural textures. The TFCM is a coding scheme that transforms an image into a feature image, in which each pixel is encoded by TFCM into a texture feature number (TFN) that represents a certain type of local texture. The TFN of each pixel in the feature image is generated based on a 3×3 texture unit as well as the gray-level variations of its eight surrounding pixels. The TFN histogram and TFN cooccurrence matrix are derived to generate many texture features for texture classification. The texture features of a gray-level cooccurrence matrix (GLCM), texture spectrum (TS), and cross-diagonal texture matrix (CDTM) have been used for comparison in discriminating natural texture images in experiments based on minimum distance and Bayesian classifiers. Experimental results reveal that the features of the TFCM are superior to the ones of the other three methods for classification.