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Proceedings Paper

Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition
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Paper Abstract

We propose an invariant descriptor for recognizing complex patterns and objects composed of closed regions such as printed Chinese characters. The method transforms a 2D image into 1D line moments, performs wavelet transform on the moments, and then applies Fourier transform on each level of the wavelet coefficients and the average. The essential advantage of the descriptor is that a multiresolution querying strategy can be employed in the recognition process and that it is invariant to shift, rotation, and scaling of the original image. Experimental results show that the descriptor proposed in this paper is a reliable tool for recognizing Chinese characters.

Paper Details

Date Published: 3 April 1997
PDF: 6 pages
Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271746
Show Author Affiliations
Tien D. Bui, Concordia Univ. (Canada)
Guangyi Chen, Concordia Univ. (Canada)


Published in SPIE Proceedings Vol. 3078:
Wavelet Applications IV
Harold H. Szu, Editor(s)

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