An Extension of 3D Zernike Moments for Shape Description and Retrieval of Maps Defined in Rectangular Solids

Atilla Sit, Julie C. Mitchell, George N. Phillips, Stephen J. Wright

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Zernike polynomials have been widely used in the description and shape retrieval of 3D objects. These orthonormal polynomials allow for efficient description and reconstruction of objects that can be scaled to fit within the unit ball. However, maps defined within box-shaped regions ¶ for example, rectangular prisms or cubes ¶ are not well suited to representation by Zernike polynomials, because these functions are not orthogonal over such regions. In particular, the representations require many expansion terms to describe object features along the edges and corners of the region. We overcome this problem by applying a Gram-Schmidt process to re-orthogonalize the Zernike polynomials so that they recover the orthonormality property over a specified box-shaped domain. We compare the shape retrieval performance of these new polynomial bases to that of the classical Zernike unit-ball polynomials.

Original languageEnglish
Pages (from-to)75-89
Number of pages15
JournalComputational and Mathematical Biophysics
Volume1
Issue number2013
DOIs
StatePublished - Apr 16 2013
Externally publishedYes

Keywords

  • 3D shape retrieval
  • Electron Microscopy Data Bank
  • Gram-Schmidt orthogonalization
  • Zernike polynomials
  • reconstruction

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