Abstract

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance. Such variations e ect texture feature images and can dramatically increase the failure rates of texture classifiers. In a previous paper we presented theory and experimental results that showed that changes in illuminant tilt angle cause texture clusters to describe Lissajous's ellipses in feature space. In this paper we use this model to develop a classifier that can classify surface textures imaged under unknown illumination tilt angles. In experiments with 30 real textures classification rates of over 99% were achieved.

Citations