3 April 1997 Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tien D. Bui, Tien D. Bui, Guangyi Chen, Guangyi Chen, } "Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition", Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271746; https://doi.org/10.1117/12.271746
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