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

Tien D. Bui; Guangyi Chen

doi:10.1117/12.271746

3 April 1997 Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition

Tien D. Bui, Guangyi Chen

Proceedings Volume 3078, Wavelet Applications IV; (1997) https://doi.org/10.1117/12.271746
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Tien D. Bui and Guangyi Chen "Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition", Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); https://doi.org/10.1117/12.271746

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