Abstract
Zernike moments are one of the most effective orthogonal, rotation-invariant moments in continuous space. Unfortunately, the digitization process necessary for use with digital imagery results in compromised orthogonality. In this work, we introduce improved digital Zernike moments that exhibit much better orthogonality, while preserving their inherent invariance to rotation. We then propose a novel pattern recognition algorithm that is based on the improved digital Zernike moments. With the improved orthogonality, targets can be represented by fewer moments, thus minimizing computational complexity. Additionally, the rotation invariance enables our algorithm to recognize targets with arbitrary orientation. Because our algorithm eliminates the segmentation step that is typically applied in other techniques, it is better suited to low-quality imagery. Simulations on real images demonstrate these aspects of the proposed algorithm.
Original language | English (US) |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
Editors | D.P. Casasent, T.-H. Chao |
Pages | 211-220 |
Number of pages | 10 |
Volume | 5816 |
DOIs | |
State | Published - 2005 |
Event | Optical Pattern Recognition XVI - Orlando, FL, United States Duration: Mar 31 2005 → Apr 1 2005 |
Other
Other | Optical Pattern Recognition XVI |
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Country/Territory | United States |
City | Orlando, FL |
Period | 3/31/05 → 4/1/05 |
Keywords
- Feature
- Image reconstruction
- Moments
- Pattern recognition
- Zernike moments
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics