JEI Letters

Rock image classification using color features in Gabor space

[+] Author Affiliations
Leena Lepistö, Iivari Kunttu, Ari Visa

Tampere University of Technology, Institute of Signal Processing, P.O. Box 553, FI-33101 Tampere, Finland

J. Electron. Imaging. 14(4), 040503 (December 21, 2005). doi:10.1117/1.2149872
History: Received June 03, 2005; Revised August 04, 2005; Accepted September 02, 2005; Published December 21, 2005; Online December 21, 2005
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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.

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© 2005 SPIE and IS&T

Citation

Leena Lepistö ; Iivari Kunttu and Ari Visa
"Rock image classification using color features in Gabor space", J. Electron. Imaging. 14(4), 040503 (December 21, 2005). ; http://dx.doi.org/10.1117/1.2149872


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