Texture recognition via autoregression

Abstract

This article considers the image processing problem of texture recognition. It is shown that a chi-square test based upon a two-dimensional autoregressive model can be derived and can be used to test for differences between certain types of micro-textures. The chi-square test cannot be used with macro-textures, and another autoregressive-based distance measure is derived which is more suitable for these cases. It is shown experimentally that this distance measure affords a reliable means of classifying a broad class of micro- and macro-textures using a nearest-neighbour type of approach. © 1982.