PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Natural Material Segmentation and Classification Using Polarisation
Nitya Subramaniam, Gule Saman and Edwin Hancock
In: Pattern Recognition and Image Analysis - 5th Iberian Conference,IbPRIA 2011, June 8-10, 2011, Las Palmas de Gran Canaria, Spain.

Abstract

This paper uses polarisation information for surface segmentation based on material reflectance characteristics. Both polarised and unpolarised light is used, and the method is hence applicable to both specular or diffuse polarisation. We use moments to estimate the mean-intensity, polarisation and phase from images obtained with multiple polariser orientations. From the Fresnel theory, the azimuth angle of the surface normal is determined by the phase angle and for a limited range of refractive index the zenith angle is determined by the degree of polarisation. Using these properties, we show how the angular distribution of the mean intensity for remitted light can be parameterised using spherical harmonics. We explore two applications of our technique, namely a) detecting skin lesions in damaged fruit, and b) exploiting spherical harmonic co-efficients to segment surfaces into regions of different material composition using normalized graph cuts.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:8534
Deposited By:Edwin Hancock
Deposited On:13 February 2012