Local Binary Pattern with Hyperparameter Tuned Support Vector Machine for Fingerprint Classification

被引：0
|
作者：
Chougule, Abhijeet [1 ]
Shah, Medha [1 ]
机构：
[1] Walchand Coll Engn, Comp Sci & Engn, Sangli, India
来源：
PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS) | 2019年
关键词：
Local Binary Pattern(LBP); Support Vector Machine(SVM); Hyperparameter Tuning; Fingerprint Liveness Detection; Machine Learning;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In recent times fingerprint authentication has become essential part of many organisation. With increase in use the risk of spoofing the fingerprint is also increased. Previously many software approaches has been used to solve this problem. Hyperparameter tuning shows improvement by Increase in Accuracy Score(IAS%) upto 27.43 %. The proposed model of Local Binary Pattern with Hyperparameter tuned Support Vector Machine achieves Average Accuracy Score(AAS) of around 98.69% on LivDet 2009, 96.39% on LivDet 2011, 97.57% on LivDet 2013, 94.84% on LivDet 2015 dataset.
引用
收藏
页码：1084 / 1087
页数：4
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