Title :
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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4959990
