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
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Image reconstruction from a complete set of similarity invariants extracted from complex moments
Pattern Recognition Letters
Image Analysis Using Hahn Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image analysis by Bessel-Fourier moments
Pattern Recognition
Radial Tchebichef moment invariants for image recognition
Journal of Visual Communication and Image Representation
Image analysis by Tchebichef moments
IEEE Transactions on Image Processing
Image analysis by Krawtchouk moments
IEEE Transactions on Image Processing
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As the variation of parameters in Jacobi polynomial, Jacobi-Fourier moments can form various types of orthogonal moments: Legendre-Fourier moments, Orthogonal Fourier-Mellin moments, Zernike moments, pseudo-Zernike moments, and so on. In this paper, we present a generic approach based on Jacobi-Fourier moments for scale and rotation invariant analysis of radial orthogonal moments, named Jacobi-Fourier moment invariants (JFMIs). It provides a fundamental mathematical tool for invariant analysis of the radial orthogonal moments since Jacobi-Fourier moments are the generic expressions of radial orthogonal moments. Theoretical and experimental results also show the superiority of the proposed method and its robustness to noise in comparison with some exist methods.