DocumentCode
1470405
Title
Polarization-based material classification from specular reflection
Author
Wolff, Lawrence B.
Author_Institution
Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
Volume
12
Issue
11
fYear
1990
fDate
11/1/1990 12:00:00 AM
Firstpage
1059
Lastpage
1071
Abstract
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
Keywords
computer vision; computerised pattern recognition; computerised picture processing; light polarisation; printed circuit testing; reflectometry; Fresnel reflectance model; PC testing; dielectric material surfaces; material classification; metal surfaces; passive sensing; polarization Fresnel ratio; polarization-reflectance model; polarizing filter; specular reflection; transmitted radiance; Cameras; Computer vision; Conducting materials; Dielectric materials; Fresnel reflection; Inspection; Machine vision; Optical polarization; Optical reflection; Passive filters; Printed circuits; Reflectivity; Sensor phenomena and characterization;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.61705
Filename
61705
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