Circularly orthogonal moments for geometrically robust image watermarking
Pattern Recognition
Human Lips as Emerging Biometrics Modality
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
A unified methodology for the efficient computation of discrete orthogonal image moments
Information Sciences: an International Journal
On the accuracy of image normalization by Zernike moments
Image and Vision Computing
Testing for image symmetries: with application to confocal microscopy
IEEE Transactions on Information Theory
A study of Zernike invariants for content-based image retrieval
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
A zernike moment phase-based descriptor for local image representation and matching
IEEE Transactions on Image Processing
Algorithms for fast computation of Zernike moments and their numerical stability
Image and Vision Computing
Fast computation of orthogonal Fourier---Mellin moments in polar coordinates
Journal of Real-Time Image Processing
Discrete circular mapping for computation of Zernike moments
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Pattern Recognition and Image Analysis
Error analysis and accurate calculation of rotational moments
Pattern Recognition Letters
Accurate calculation of Zernike moments
Information Sciences: an International Journal
A novel speech content authentication algorithm based on Bessel-Fourier moments
Digital Signal Processing
Error Analysis in the Computation of Orthogonal Rotation Invariant Moments
Journal of Mathematical Imaging and Vision
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An algorithm for high-precision numerical computation of Zernike moments is presented. The algorithm, based on the introduced polar pixel tiling scheme, does not exhibit the geometric error and numerical integration error which are inherent in conventional methods based on Cartesian coordinates. This yields a dramatic improvement of the Zernike moments accuracy in terms of their reconstruction and invariance properties. The introduced image tiling requires an interpolation algorithm which turns out to be of the second order importance compared to the discretization error. Various comparisons are made between the accuracy of the proposed method and that of commonly used techniques. The results reveal the great advantage of our approach