Invariant Fourier-wavelet descriptor for pattern recognition
We present a novel set of descriptors for recognizing complex patterns such as roadsigns, keys, aircrafts, characters, etc. Given a pattern, we first transform it to polar coordinate (r, theta) using the centre of mass of the pattern as origin. We then apply the Fourier transform along the axis of polar angle theta and the wavelet transform along the axis of radius r. The features thus obtained are invariant to translation, rotation, and scaling. As an example, we apply the method to a database of 85 printed Chinese characters. The result shows that the Fourier-wavelet descriptor is an efficient representation which can provide for reliable recognition. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
pattern recognition fourier transform wavelet transform feature extraction invariant descriptor multiresolution analysis