Orthogonal moment functions based on Tchebichef polynomials have found several applications in the field of image analysis because of their superior feature representation capabilities. Local features represented by such moments could also be used in the design of efficient texture descriptors. This chapter introduces a novel method of constructing feature vectors from orthonormal Tchebichef moments evaluated on 5x5 neighborhoods of pixels, and encoding the texture information as a Lehmer code that represents the relative strengths of the evaluated moments. The features will be referred to as Local Tchebichef Moments (LTMs). The encoding scheme provides a byte value for each pixel, and generates a gray-level "LTM-image" of the input image. The histogram of the LTM-image is then used as the texture descriptor for classification. The theoretical framework as well as the implementation aspects of the descriptor are discussed in detail.