Estimating surface characteristics and extracting features from polarisation

Authors:
Lichi Zhang;Edwin R. Hancock;Jing Wu
Affiliations:
Department of Computer Science, University of York, UK,School of Computer Science and Informatics, Cardiff University, UK;Department of Computer Science, University of York, UK,School of Computer Science and Informatics, Cardiff University, UK;Department of Computer Science, University of York, UK,School of Computer Science and Informatics, Cardiff University, UK
Venue:
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2012

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Abstract

In this paper we develop a practical method for estimating shape, color and reflectance using only three images taken under polarised light. We develop a novel and practical framework to optimise the estimates and eliminate the redundant information, then investigate three different methods to compare their class discriminating capacities. We present experiment to demonstrate the validity of the proposed method for a database of fruit objects from 5 different classes, and we show that the proposed method is capable of accurately extracting the features of the input examples. The framework can further be applied in a variety fields of computer vision and pattern recognition domains including object recognition and classification.