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Proceedings Paper

Importance of the texture features in a query from spectral image databases
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Paper Abstract

A new, semantically meaningful technique for querying the images from a spectral image database is proposed. The technique is based on the use of both color- and texture features. The color features are calculated from spectral images by using the Self-Organizing Map (SOM) when methods of Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) are used for constructing the texture features. The importance of texture features in a querying is seen in experimental results, which are given by using a real spectral image database. Also the differences between the results gained by the use of co-occurrence matrix and LBP are introduced.

Paper Details

Date Published: 17 January 2006
PDF: 10 pages
Proc. SPIE 6062, Spectral Imaging: Eighth International Symposium on Multispectral Color Science, 60620R (17 January 2006); doi: 10.1117/12.643245
Show Author Affiliations
Oili Kohonen, Univ. of Joensuu (Finland)
Markku Hauta-Kasari, Univ. of Joensuu (Finland)

Published in SPIE Proceedings Vol. 6062:
Spectral Imaging: Eighth International Symposium on Multispectral Color Science
Mitchell R. Rosen; Francisco H. Imai; Shoji Tominaga, Editor(s)

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