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Orthogonal Rotation Invariant Moments and Transforms for Pattern Recognition and Computer Vision Applications
Various radial moments and polar harmonic transforms such as polar complex exponential transforms, polar cosine transforms and polar sine transforms satisfy orthogonal principle. By virtue of which these moments and transforms possess minimum information redundancy and thereby exhibit a good characteristic of image representation. In this paper, a complete comparative analysis is performed by considering image reconstruction capability of each individual moment and transform. The orthogonal properties of above mentioned moments along with the causes of their reconstruction error, numerical stability and invariance are described.
Keywords
Zernike Moments, Pseudo Zernike Moments, Orthogonal Fourier Mellin Moments, Radial Harmonic Fourier Moments, Chebyshev-Fourier Moments, Polar Harmonic Transforms.
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