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Journal of Electronic Imaging • Open Access

Rock image classification using color features in Gabor space

Paper Abstract

In image classification, the common texture-based methods are based on image gray levels. However, the use of color information improves the classification accuracy of the colored textures. In this paper, we extract texture features from the natural rock images that are used in bedrock investigations. A Gaussian bandpass filtering is applied to the color channels of the images in RGB and HSI color spaces using different scales. The obtained feature vectors are low dimensional, which make the methods computationally effective. The results show that using combinations of different color channels, the classification accuracy can be significantly improved.

Paper Details

Date Published: 1 October 2005
PDF: 3 pages
J. Electron. Imaging. 14(4) 040503 doi: 10.1117/1.2149872
Published in: Journal of Electronic Imaging Volume 14, Issue 4
Show Author Affiliations
Leena Lepistö, Tampereen Teknillinen Yliopisto (Finland)
Iivari Kunttu, Tampereen Teknillinen Yliopisto (Finland)
Ari J.E. Visa, Tampereen Teknillinen Yliopisto (Finland)


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