Invariant Fourier-wavelet descriptor for pattern recognition

被引:79
作者
Chen, GY [1 ]
Bui, TD [1 ]
机构
[1] Concordia Univ, Dept Comp Sci, Montreal, PQ H3G 1M8, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
feature extraction; Fourier transform; invariant descriptor; multiresolution analysis; pattern recognition; wavelet transform;
D O I
10.1016/S0031-3203(98)00148-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1083 / 1088
页数:6
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