Surface Texture Recognition by Surface Rendering

A model-based texture recognition system which classifies image textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source Colour Photometric Stereo (CPS), used to generate 2D image textures as they would have appeared if imaged under different imaging geometries. The proposed recognition system combines co-ocurrence matrices for feature extraction with a Nearest Neighbour classifier. The use of the co-occurrence matrices instead of filtering methods for feature extraction allows us to utilise only pixels for which valid information has been extracted by CPS. The validity of the method is demonstrated by classifying texture images captured under different imaging geometries than the reference images in the database. Moreover, the process of recognition allows one to guess the approximate direction of the illumination used to capture the test image.