Image analysis by Bessel-Fourier moments

  • Authors:

  • Bin Xiao;Jian-Feng Ma;Xuan Wang

  • Affiliations:

  • The Key Laboratory of Computer Networks and Information Security, Ministry of Education, Xidian University, Xi'an 710071, China and School of Physics & Electrical Information Engineering, Ningxia ...;The Key Laboratory of Computer Networks and Information Security, Ministry of Education, Xidian University, Xi'an 710071, China;School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710062, China

  • Venue:
  • Pattern Recognition
  • Year:
  • 2010

Quantified Score

Hi-index 0.02

Visualization

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.