Synthetic biometrics: A survey

被引:0
|
作者
Yanushkevich, S. N. [1 ]
机构
[1] Univ Calgary, Biometr Technol Lab, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada
来源
2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 | 2006年
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
This brief survey addresses the state-of-the-art techniques of inverse biometrics, which deals with synthesis of biometric data. It reports on genesis of synthetic biometric, advanced methods, and open application-specific problems. Currently deployed biometric systems use comprehensive methods and algorithms (such as pattern recognition, decision making, database searching, etc.) to analyze biometric data collected from individuals. We consider the inverse task, synthesis of artificial biometric data. These biologically meaningful data are useful, for example, for testing the biometric tools, and for enhancing the security of biometric systems. The synthetic data replicate all possible instances of otherwise unavailable data, thus, creating a variety of samples for testing. Properly created artificial biometric data provides a basis for enhancing security through the detailed and controlled modeling of a wide range of training skills, strategies and tactics of a hypothetical robber or forger. Databases of synthetic biometric data also serve for simulation in forensic systems.
引用
收藏
页码:676 / 683
页数:8
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