The segmentation of rough surfaces using their reflectance properties is considered. We present a technique to estimate the orientation of surface facets whose reflectance functions are unknown. The reflectance characteristics of each facet are estimated individually allowing this technique to be applied to non-homogeneous surfaces. Non-Lambertian components are attenuated allowing shape estimation with classical photometric stereo. Simulations with rough surfaces rendered with Phong's model indicate that this approach extends the range of reflectance functions to which classical photometric stereo can be applied. The recovered surface derivatives, together with the original intensity images are used to construct reflectance maps. These are used as features for segmentation. A reflectance based classifier is found to be more accurate than an intensity classifier.
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