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Gabor Filtering of Complex Hue/Saturation Images for Color Texture Classification

  • Objective: Complex hue/saturation images as a new approach for color texture classification using Gabor filters are introduced and compared with common techniques. Method: The interpretation of hue and saturationas polar coordinates allows direct use of the HSV-colorspace for Fourier transform. This technique is applied for Gabor feature extraction of color textures. In contrast to other color features based on the RGB-colorspace [1] the combination of color bands is done previous to the filtering. Results: The performance of the new HS-featuresis compared with that of RGB based as well as grayscale Gabor features by evaluating the classifi-cation of 30 natural textures. The new HS-featuresshow same results like the best RGB features but allow a more compact representation. On the averagethe color features improve the results of grayscale features. Conclusion: The consideration of the color information enhances the classification of color texture. The choice of colorspace cannot be adjudged finally, but the introduced features suggest the use of the HSV-colorspace with less features than RGB.

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Metadaten
Author:Christoph PalmORCiDGND, Daniel Keysers, Thomas M. Lehmann, Klaus Spitzer
URL / DOI:http://www.keysers.net/daniel/files/JCIS2000_palm.pdf
Parent Title (English):Proceedings of the 5th Joint Conference on Information Science (JCIS) 2, The Association for Intelligent Machinery, Atlantic City, NJ, 2000
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2000
Release Date:2020/06/05
First Page:45
Last Page:49
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Regensburg Medical Image Computing (ReMIC)
Publication:Externe Publikationen
research focus:Lebenswissenschaften und Ethik
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG