Classifying Surface Texture while Simultaneously Estimating Illumination Direction

摘要

We propose a novel classifier that both classifies surface texture and simultaneously estimates the unknown illumination conditions. A new formal model of the dependency of texture features on lighting direction is developed which shows that their mean vectors are trigonometric functions of the illuminations’ tilt and slant angles. This is used to develop a probabilistic description of feature behaviour which forms the basis of the new classifier. Given a feature set from an image of an unknown texture captured under unknown illumination conditions the algorithm first estimates the most likely illumination direction for each possible texture class. These estimates are used to calculate the class likelihoods and the classification is made accordingly.