Issue No. 11 - November (1990 vol. 12)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.61705
<p>A computationally simple yet powerful method for distinguishing metal and dielectric material surfaces from the polarization characteristics of specularly reflected light is introduced. The method is completely passive, requiring only the sensing of transmitted radiance of reflected light through a polarizing filter positioned in multiple orientations in front of a camera sensor. Precise positioning of lighting is not required. An advantage of using a polarization-based method for material classification is its immunity to color variations, which so commonly exist on uniform material samples. A simple polarization-reflectance model, called the Fresnel reflectance model, is developed. The fundamental assumptions are that the diffuse component of reflection is completely unpolarized and that the polarization state of the specular component of reflection is dictated by the Fresnel reflection coefficients. The material classification method presented results axiomatically from the Fresnel reflectance model, by estimating the polarization Fresnel ratio. No assumptions are required about the functional form of the diffuse and specular components of reflection. The method is demonstrated on some common objects consisting of metal and dielectric parts.</p>
metal surfaces; passive sensing; PC testing; material classification; specular reflection; dielectric material surfaces; transmitted radiance; polarizing filter; polarization-reflectance model; Fresnel reflectance model; polarization Fresnel ratio; computer vision; computerised pattern recognition; computerised picture processing; light polarisation; printed circuit testing; reflectometry
L. Wolff, "Polarization-Based Material Classification from Specular Reflection," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 12, no. , pp. 1059-1071, 1990.