Degraded image analysis using Zernike moment invariants

Author

Ji, Hanjie ; Zhu, Hongqing

Author_Institution

Dept. of Electron. & Commun. Eng., East China Univ. of Sci. & Technol., Shanghai

fYear

2009

fDate

19-24 April 2009

Firstpage

1941

Lastpage

1944

Abstract

In real imaging system, the observed image is usually corrupted by blurring, spatial degradations. The classical recognition methods in degraded image analysis are to obtain blur invariants based on geometric moments or complex moments. In this paper, we introduce blur invariants based on Zernike moments which are orthogonal over a unit circle. Both the expression of Zernike moments of blurred image and the set of blur invariants based on Zernike moments are presented and proved mathematically. Compared with the pattern classification results of complex moments, the experimental results of Zernike moment demonstrate that the proposed method performs well in object and pattern recognition.

Keywords

Zernike polynomials; image classification; image restoration; Zernike moment invariants; blur invariants; classical recognition methods; degraded image analysis; pattern classification; real imaging system; Convolution; Degradation; Equations; Image analysis; Image recognition; Kernel; Layout; Pattern classification; Pattern recognition; Polynomials; Zernike moments; blur invariants; classification; pattern recognition; radial moments;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Conference_Location

Taipei

ISSN

1520-6149

Print_ISBN

978-1-4244-2353-8

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2009.4959990

Filename

4959990