Invariant 2D object recognition using the wavelet modulus maxima

被引:36
作者
Khalil, MI [1 ]
Bayoumi, MM [1 ]
机构
[1] Queens Univ, Dept Elect & Comp Engn, Kingston, ON K7L 3N6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
pattern recognition; wavelet modulus maxima representation; Lipschitz exponents;
D O I
10.1016/S0167-8655(00)00046-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a technique is proposed to recognize 2D objects under translation, rotation, and scale transformations. The technique is based on the continuous wavelet transform and neural networks. Experimental results are presented and compared with some traditional methods. The experimental results showed that this refined technique was successful in classifying the objects under consideration and that it outperformed those traditional methods especially in the presence of noise. (C) 2000 Published by Elsevier Science B.V. All rights reserved.
引用
收藏
页码:863 / 872
页数:10
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