Color scene classification by Zernike moment invariants

Yongjun Zhou; Mehmet Celenk

doi:10.1117/12.438274

28 August 2001 Color scene classification by Zernike moment invariants

Yongjun Zhou, Mehmet Celenk

Proceedings Volume 4388, Visual Information Processing X; (2001) https://doi.org/10.1117/12.438274
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

Hu and Zernike moments have been widely used in many shape recognition and object classification tasks. The Hu moments are the projections of an image I(x,y) on the basis functions formed by the monomials xPyq of non-orthogonal nature. Zernike moments are computed based on a set of orthogonal polynomials over the interior of the unit circle x²+y²<EQ1 in the image center using from the image pixels mapped into the unit circle and ignoring pixels falling outside the unit circle. Although comparative studies show that the Zernike polynomials have better noise performance in the context of character recognition and capable of coping both geometry as well as illumination invariance in the context of multispectral texture classification, there is no study conducted focusing on the application of Zernike moments to color image databases. In this paper, we study the performance of Zernike moments against the moments of Hu, in the context of RTSS (Rotation, translation, scaling)-invariant color scene classification, and determine which method behaves better in noisy visual information system. The method described here relies on the principal component analysis (PCA) and the discrete Karhunen-Loeve (KL) transformation for converting a vector- valued color image into a gray-level scale representation. For a selected set of images involving different models of vehicles, we demonstrate experimentally that the first two Zernike moments are highly immune to the sensory noise and also invariant to changes in the position, orientation, and size. They provide better classification power than the Hu moments in the presence of Gaussian noise.

Citation Download Citation

Yongjun Zhou and Mehmet Celenk "Color scene classification by Zernike moment invariants", Proc. SPIE 4388, Visual Information Processing X, (28 August 2001); https://doi.org/10.1117/12.438274

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KEYWORDS

Principal component analysis

Scene classification

Image sensors

Sensors

Zernike polynomials

Databases

Image classification

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