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Proceedings Paper

Metal-dielectric object classification by combining polarization property and surface spectral reflectance
Author(s): Shoji Tominaga; Hideki Kadoi; Keita Hirai; Takahiko Horiuchi
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Paper Abstract

We propose a method for automatically classifying multiple objects in a natural scene into metal or dielectric. We utilize polarization property in order to classify the objects into metal and dielectric, and surface-spectral reflectance in order to segment the scene image into different object surface regions. An imaging system is developed using a liquid crystal tunable filter for capturing both polarization and spectral images simultaneously. Our classification algorithm consists of three stages; (1) highlight detection based on luminance threshold, (2) material classification based on the spatial distribution of the degree of polarization at the highlight area, and (3) image segmentation based on illuminant-invariant representation of the spectral reflectance. The feasibility of the proposed method is examined in detail in experiments using real-world objects.

Paper Details

Date Published: 4 February 2013
PDF: 8 pages
Proc. SPIE 8652, Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications, 86520E (4 February 2013); doi: 10.1117/12.2005638
Show Author Affiliations
Shoji Tominaga, Chiba Univ. (Japan)
Hideki Kadoi, Chiba Univ. (Japan)
Keita Hirai, Chiba Univ. (Japan)
Takahiko Horiuchi, Chiba Univ. (Japan)

Published in SPIE Proceedings Vol. 8652:
Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu; Alessandro Rizzi, Editor(s)

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