Invariant Image Recognition Using Radial Jacobi Moment Invariants

Author

Xiao, Bin ; Ma, Jian-feng ; Cui, Jiang-Tao

Author_Institution

Key Lab. of Comput. Networks & Inf. Security, Xidian Univ., Xi´´an, China

fYear

2011

fDate

12-15 Aug. 2011

Firstpage

280

Lastpage

285

Abstract

As orthogonal moments in the polar coordinate, radial orthogonal moments such as Zernike, pseudo-Zernike and orthogonal Fourier-Mellin moments have been successfully used in the field of pattern recognition. However, the scale and rotation invariant property of these moments has not been studied. In this paper, we present a generic approach based on Jacobi-Fourier moments for scale and rotation invariant analysis of radial orthogonal moments. 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. Experimental results show the efficiency and the robustness to noise of the proposed method for recognition tasks.

Keywords

Jacobian matrices; image recognition; Jacobi-Fourier moments; invariant analysis; invariant image recognition; pattern recognition; polar coordinate; radial Jacobi moment invariants; radial orthogonal moments; Accuracy; Image recognition; Image reconstruction; Jacobian matrices; Noise; Pattern recognition; Polynomials; Invariant features; Invariant recognition; Jacobi-Fourier moments; Radial orthogonal moments;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2011 Sixth International Conference on

Conference_Location

Hefei, Anhui

Print_ISBN

978-1-4577-1560-0

Electronic_ISBN

978-0-7695-4541-7

Type

conf

DOI

10.1109/ICIG.2011.62

Filename

6005596