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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 1/2013

01.02.2013 | Theoretical Advances

Rotation invariant features for color texture classification and retrieval under varying illumination

verfasst von: B. Sathyabama, M. Anitha, S. Raju, V. Abhaikumar

Erschienen in: Pattern Analysis and Applications | Ausgabe 1/2013

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Abstract

This article proposes a new quaternion-based method for rotation invariant color texture classification under illumination variance with respect to direction and spectral band. The color of an object varies according to the spectral power distribution, object-illumination, and viewing geometry of the light source. The quaternion representation of color is shown to be effective, which treats color channels as single unit rather than separate components. New texture signatures are extracted by calculating the norm of the Quaternion fourier spectrum. These signatures are proved to be invariant under image rotation and illumination rotation. Moreover, these features are also invariant to the color spaces. The robustness of different color spaces against varying illumination in color Texture classification with 45 samples of 15 outex texture classes are examined. Comparative results show that the proposed method is efficient in rotation invariant texture classification.
Vorheriger Artikel Expectation-maximization algorithms for inference in Dirichlet processes mixture
Nächster Artikel A unifying methodology for the evaluation of neural network models on novelty detection tasks

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Metadaten
Titel
Rotation invariant features for color texture classification and retrieval under varying illumination
verfasst von
B. Sathyabama
M. Anitha
S. Raju
V. Abhaikumar
Publikationsdatum
01.02.2013
Verlag
Springer-Verlag
Erschienen in
Pattern Analysis and Applications / Ausgabe 1/2013
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-011-0207-0

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