Analysis of Modern Static Methods of Biometric Identification
https://doi.org/10.21869/2223-1560-2019-23-1-84-94
Abstract
Purpose of reseach. Modern data collection systems use mobile automated devices, the data from which is encrypted in the data center. Biometric identification methods have several advantages as means of information security in the data center. In particular they are characterized by high reliability, since it is difficult to compromise or lose biometric data.
Methods. The method of biometric identification of facial geometry is proposed in the article. This method allows you to build a 3D model of a human face based on 2D images. To determine the accuracy of the biometric identification method, quantitative characteristics of FAR and FRR are proposed. FAR - false acception rate - determines the percentage of situations when the system allows access to a user who is not registered in the database. FRR - false rejection rate - determines the percentage of situations when the system denies access to a user with correct biometric data. There are other characteristics used in the selection of biometric identification systems. They are the ease of use, the speed of the system, the influence of environmental factors on it, the cost of the system and others.
Results. The following well-known static identification methods are considered: fingerprint identification method, eye retina identification method, eye iris identification method, face geometry identification method as well as a hand vein identification method. The comparative characteristics of each of them are given. This new method is proposed to increase the accuracy and speed of biometric identification.
Conclusion. The article analyzes the modern biometric identification tools of static type. Various parameters for determining the effectiveness of bio-metric identification methods are considered. The principles, on which each of these methods is based, as well as the main advantages and disadvantages, are presented.About the Authors
I. V. KalutskiyRussian Federation
Igor V. Kalutskiy, Candidate of Engineering Sciences, Associate Professor
94, 50 Let Oktyabrya str., Kursk, 305040
Yu. S. Matiushin
Russian Federation
Yuriy S. Matiushin, Student
94, 50 Let Oktyabrya str., Kursk, 305040
S. V. Spevakova
Russian Federation
Svetlana V. Spevakova, Post-Graduate Student
94, 50 Let Oktyabrya str., Kursk, 305040
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Review
For citations:
Kalutskiy I.V., Matiushin Yu.S., Spevakova S.V. Analysis of Modern Static Methods of Biometric Identification. Proceedings of the Southwest State University. 2019;23(1):84-94. (In Russ.) https://doi.org/10.21869/2223-1560-2019-23-1-84-94