Abstract: Traditional stereo correspondence algorithms rely heavily on the Lambertian model of diffuse reflectance. While this diffuse assumption is generally valid for much of an image, processing of regions that contain specular refleclions can result in severe matching errors. We addressed the problem of binocular stereo dense matching in the presence of specular reflections by introducing a novel correspondence measurement which separates reflection components based on chromaticity. Accurate depth can be estimated for both diffuse and specular regions. Unlike the previous works which seek to eliminate or avoid specular reflections using image preprocessing or multibaseline stereo, our approach works in its presence. Experiments with both synthetic demonstrate the effectiveness and robustness of our approach.

Key words: Machine vision, Stereo matching, Diffuse reflection, Specular reflection, Chromaticity