Illumination Invariant Recognition of Color Texture Using Correlation and Covariance Functions

Authors:
Mohammed Al-Rawi;Yang Jie
Affiliations:
-;-
Venue:
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Year:
2001

Citing 12
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Abstract

In this paper, we derive a complete set of Zernike moment correlation functions used to capture spatial structure of a color texture. The set of moment correlation functions is grouped into moment correlation matrices to be used in illumination invariant recognition of color texture. For any change in the illumination, the moment correlation matrices are related by a linear transformation. Circular and non-circular correlation are discussed and comparisons with a previously suggested color covariance functions have been carried out using about 600 different illumintaions and rotations textures images. Using moment correlation matrices in the invariant recognition of color texture, the process can promise in high computation efficiency as well as recognition accuracy. The derived correlation invariants in proposed as a general formalism that can be used directly with other kinds of complex moments, e.g. Fourier Mellin, pseudo Zernike, disc-harmonic coefficients, and wavelet moments, to obtain moment correlation based invariants.