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Proceedings Paper

Image invariant moments for shape description
Author(s): Yunlong Sheng; Ziliang Ping; RiGeng Wu
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Paper Abstract

We show that the transformation with radial polynomial and circular Fourier kernel of two-dimensional image can generate image moments, which are invariant to rotation, translation and scale changes. Among them the orthogonal Fourier-Mellin moments using the generalized Jacobi radial polynomials show better performance that the Zernike moments. We introduce new Chebyshev-Fourier moments using Chebyshev radial polynomials, which improve the behavior of the orthogonal Fourier-Mellin moments in regions close to the center of image. Experimental results are shown for the image description performance of the Chebyshev-Fourier moments in terms of image reconstruction errors and sensitivity to noise. In the cases of binary or contour shapes the Fourier-Mellin moments of single orders are able to describe and reconstruct the shapes.

Paper Details

Date Published: 16 September 2002
PDF: 10 pages
Proc. SPIE 4929, Optical Information Processing Technology, (16 September 2002); doi: 10.1117/12.483220
Show Author Affiliations
Yunlong Sheng, COPL/Univ. Laval (Canada)
Ziliang Ping, Inner Mongolia Normal Univ. (China) and Univ. Laval (China)
RiGeng Wu, Beijing Univ. (China)

Published in SPIE Proceedings Vol. 4929:
Optical Information Processing Technology
Guoguang Mu; Francis T. S. Yu; Suganda Jutamulia, Editor(s)

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