On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Accuracy of Zernike Moments for Image Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multibit Geometrically Robust Image Watermark Based on Zernike Moments
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
On the computational aspects of Zernike moments
Image and Vision Computing
Circularly orthogonal moments for geometrically robust image watermarking
Pattern Recognition
Robust image watermarking using local Zernike moments
Journal of Visual Communication and Image Representation
Numerical experiments on the accuracy of rotation moments invariants
Image and Vision Computing
Invariant image watermark using Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
Real-time computation of Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
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Zernike moments are widely applied in digital image processing fields based on many desirable properties, such as rotational invariance, noise robust and efficient representation of pattern. On the computational analysis of Zernike moment is challenging issue. From an algorithmic aspect, in this paper we investigate the effect of image rotation (including crop rotation and loose rotation) operations on Zernike moments in both theoretical and experimental ways. For the crop rotation, we suggest to extract the Zernike moments by mapping the image over a disc instead of inside a circle since the outside of an image after the crop rotation will be distorted. Referring to the loose rotation, we propose a preprocessing step (which is called image size normalization) to embed an image and its rotated versions into a predefined size of zero-value image in such a way that the effect of image size change due to loose rotation can be eliminated. By incorporating the proposed image size normalization operation, we introduce an effective extraction method of image Zernike moments against loose rotation operation. Experimental results show the validity of the proposed extraction method.