A Computation Method of Texture Regularity Using Summed-Up Distance Matching Function

Regularity is one of the main features of texture image, and it can be used for description and classification of texture images. A computation method of texture regularity based on summed-up distance matching function（SDMF） is proposed. On this basis, texture classification model for regular texture, approximate regular texture and random texture is also proposed as well as texton roughness. First of all, SDMF of the texture image is constructed. Then, significant peaks and valleys of SDMF are extracted by second derivative and threshold division. At last, texture regularity computation and classification is characterized by the quantity, position and relationship among peaks and valleys. Experiment results based on Brodatz image database show that the proposed method can effectively distinguish different regular and irregular textures and has intuitive meaning. Compared with the existing method, the proposed method is more accurate. Meanwhile, the first periodicity of SDMF can be used as texture primitive size, that makes it as an extension of computation of degree of the texture roughness.