Generic radial orthogonal moment invariants for invariant image recognition

• A generic approach of radial moments for invariant image recognition is presented.
• The proposed method is based on Jacobi–Fourier moments.
• Jacobi–Fourier moments can form various types of orthogonal moments.
• The proposed method is robust to noise distortion.

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.