Pattern recognition and image reconstruction using improved digital zernike moments

Huibao Lin, Jennie Si, Glen P. Abousleman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


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 languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsD.P. Casasent, T.-H. Chao
Number of pages10
StatePublished - 2005
EventOptical Pattern Recognition XVI - Orlando, FL, United States
Duration: Mar 31 2005Apr 1 2005


OtherOptical Pattern Recognition XVI
Country/TerritoryUnited States
CityOrlando, FL


  • Feature
  • Image reconstruction
  • Moments
  • Pattern recognition
  • Zernike moments

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics


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