Neural network based recognition by using Genetic algorithm for feature selection of enhanced fingerprints

被引：0
|
作者：
Altun, Adem Alpaslan [1 ]
Allahverdi, Novruz [1 ]
机构：
[1] Selcuk Univ, Tech Educ Fac, Dept Comp Syst Educ, TR-42031 Konya, Turkey
来源：
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT 2 | 2007年 / 4432卷
关键词：
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：
In order to ensure that the performance of a fingerprint recognition system will be powerful with respect to the quality of input fingerprint images, the enhancement of fingerprints is essential. In this study wavelet transform and contourlet transform which is a new extension of the wavelet transform in two dimensions are applied for fingerprint enhancement. In addition, feature selection is a process that chooses a subset of features from the original fingerprint features so that the feature space is optimally reduced according to a certain criterion. In this study, a Genetic Algorithms (GAs) approach to fingerprint feature selection is proposed and selected features are input to Artificial Neural Networks (ANNs) for fingerprint recognition. The performance has been tested on fingerprint recognition.
引用
收藏
页码：467 / +
页数：3
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