JOURNAL ARTICLE

Degraded image analysis using Zernike moment invariants

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 Velocity Moments Moment (physics) Artificial intelligence Image moment Computer vision Image (mathematics) Cognitive neuroscience of visual object recognition Pattern recognition (psychology) Mathematics Computer science Object (grammar) Image processing Optics Physics

Metrics

16
Cited By
1.55
FWCI (Field Weighted Citation Impact)
7
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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