ICA and BP neural network based fingerprint recognition

被引：0
|
作者：
Zhao, Lu [1 ]
Wang, Wenyong [1 ]
机构：
[1] NE Normal Univ, Inst Ideal Informat Technol, Changchun, Peoples R China
来源：
PROCEEDINGS OF THE 2013 THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND SOFTWARE ENGINEERING (ICAISE 2013) | 2013年 / 37卷
关键词：
Fingerprint recognition; strong noise; FastICA; BP neural network;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
According to the recognition of fuzzy fingerprint and the ones with strong noise, proposed a new method which combining the ICA (Independent Component Algorithm) and BP (Back Propagation) neural network. First, using the FastICA method to extract fingerprint characteristics, then classify and recognize them by a three- layers BP neural network. This method combines the local feature extraction capability of ICA, as well as the adaptive ability and robustness of BP neural network. Experiments show that this method has a higher recognition rate of the fingerprints with strong noise.
引用
收藏
页码：59 / 61
页数：3
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