Abstract
In this paper, we proposed a new set of moments based on the Bessel function of the first kind, named Bessel–Fourier moments (BFMs), which are more suitable than orthogonal Fourier–Mellin and Zernike moments for image analysis and rotation invariant pattern recognition. Compared with orthogonal Fourier–Mellin and Zernike polynomials of the same degree, the new orthogonal radial polynomials have more zeros, and these zeros are more evenly distributed. The Bessel–Fourier moments can be thought of as generalized orthogonalized complex moments. Theoretical and experimental results show that the Bessel–Fourier moments perform better than the orthogonal Fourier–Mellin and Zernike moments (OFMMs and ZMs) in terms of image reconstruction capability and invariant recognition accuracy in noise-free, noisy and smooth distortion conditions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
