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Proceedings Paper

Content-based image classification with circular harmonic wavelets
Author(s): Giovanni Jacovitti; Alessandro Neri
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Paper Abstract

Classification of an image on the basis of contained patterns is considered in a context of detection and estimation theory. To simplify mathematical derivations, image and reference patterns are represented on a complex support. This allows to convert the four positional parameters into two complex numbers: complex displacement and complex scale factor. The latter one represents isotropic dilations with its magnitude, and rotations with its phase. In this context, evaluation of the likelihood function under additive Gaussian noise assumption allows to relate basic template matching strategy to wavelet theory. It is shown that using circular harmonic wavelets simplifies the problem from a computational viewpoint. A general purpose pattern detection/estimation scheme is introduced by decomposing the images on a orthogonal basis formed by complex Laguerre-Gauss Harmonic wavelets.

Paper Details

Date Published: 8 July 1998
PDF: 12 pages
Proc. SPIE 3389, Hybrid Image and Signal Processing VI, (8 July 1998); doi: 10.1117/12.316541
Show Author Affiliations
Giovanni Jacovitti, Univ. of Rome La Sapienza (Italy)
Alessandro Neri, Univ. of Rome III (Italy)

Published in SPIE Proceedings Vol. 3389:
Hybrid Image and Signal Processing VI
David P. Casasent; Andrew G. Tescher, Editor(s)

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