Object surface recovery using a multi-light photometric stereo technique for non-Lambertian surfaces subject to shadows and specularities

Authors:
Jiuai Sun;Melvyn Smith;Lyndon Smith;Sagar Midha;Jeff Bamber
Affiliations:
Machine Vision Lab, Faculty of CEMS, University of the West of England, Bristol BS16 1QY, UK;Machine Vision Lab, Faculty of CEMS, University of the West of England, Bristol BS16 1QY, UK;Machine Vision Lab, Faculty of CEMS, University of the West of England, Bristol BS16 1QY, UK;Machine Vision Lab, Faculty of CEMS, University of the West of England, Bristol BS16 1QY, UK;Ultrasound and Optical Imaging, Institute of Cancer Research and Royal Marsden NHS Trust, Surrey SM2 5PT, UK
Venue:
Image and Vision Computing
Year:
2007

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Abstract

This paper presents a new multi-light source photometric stereo system for reconstructing images of various characteristics of non-Lambertian rough surfaces with widely varying texture and specularity. Compared to the traditional three-light photometric stereo method, extra lights are employed using a hierarchical selection strategy to eliminate the effects of shadows and specularities, and to make the system more robust. We also show that six lights is the minimum needed in order to apply photometric stereo to the entire visible surface of any convex object. Experiments on synthetic and real scenes demonstrate that the proposed method can extract surface reflectance and orientation effectively, even in the presence of strong shadows and highlights. Hence, the method offers advantages in the recovery of dichromatic surfaces possessing rough texture or deeply relieved topographic features, with applications in reverse engineering and industrial surface inspection. Experimental results are presented in the paper.