DocumentCode :
3094096
Title :
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
Link To Document :
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