Color texture classification by normalized color space representation

This paper proposes a novel approach to color texture characterization and classification. Rather than developing new textural features, we propose to derive a family of new, reduced dimensionality color spaces named P/sub 1/P/sub 2/, that allow a good classification performance by the use of classi...

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Bibliographic Details
Main Authors: Vertan, C., Boujemaa, N.
Format: Conference Proceeding
Language:English
Subjects:
Computer vision
Frequency domain analysis
Image color analysis
Image processing
Image segmentation
Image texture analysis
Physiology
Roentgenium
Signal processing algorithms
Tellurium
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Description
Summary:This paper proposes a novel approach to color texture characterization and classification. Rather than developing new textural features, we propose to derive a family of new, reduced dimensionality color spaces named P/sub 1/P/sub 2/, that allow a good classification performance by the use of classical energy-distribution features, defined in a scalar spectral domain. The dimensionality reduction approach can be traced back to color constancy normalization and the reduced ordering principle and exhibits a strong perceptual background. We develop an adaption procedure for the selection of the proper color space within the new P/sub 1/P/sub 2/ family. The overall classification performance is very promising and the proposed methodology surmounts the current color texture characterization by features extracted from the luminance spectrum only.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2000.903612