Pattern recognition and image reconstruction using improved digital Zernike moments

Huibao Lin; Jennie Si; Glen P. Abousleman

doi:10.1117/12.604076

28 March 2005 Pattern recognition and image reconstruction using improved digital Zernike moments

Huibao Lin, Jennie Si, Glen P. Abousleman

Proceedings Volume 5816, Optical Pattern Recognition XVI; (2005) https://doi.org/10.1117/12.604076
Event: Defense and Security, 2005, Orlando, Florida, United States

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.

Citation Download Citation

Huibao Lin, Jennie Si, and Glen P. Abousleman "Pattern recognition and image reconstruction using improved digital Zernike moments", Proc. SPIE 5816, Optical Pattern Recognition XVI, (28 March 2005); https://doi.org/10.1117/12.604076

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