Verifying a Chipcard-Based Biometric Identification Protocol in VSE

2006 ◽  
pp. 42-56 ◽  
Author(s):  
Lassaad Cheikhrouhou ◽  
Georg Rock ◽  
Werner Stephan ◽  
Matthias Schwan ◽  
Gunter Lassmann
Keyword(s):  
Biometric Identification

ECG-based biometric identification: some modern approaches

2016 ◽  
pp. 35-39
Author(s):  
A.A. Astapov ◽  
◽  
D.V. Davydov ◽  
A.I. Egorov ◽  
D.V. Drozdov ◽  
...  
Keyword(s):  
Biometric Identification

scholarly journals Biometric identification using knee X-rays

2009 ◽  
Vol 1 (3) ◽  
pp. 365 ◽  
Author(s):  
Lior Shamir ◽  
Shari Ling ◽  
Salim Rahimi ◽  
Luigi Ferrucci ◽  
Ilya G. Goldberg
Keyword(s):  
Biometric Identification ◽  
X Rays

CloudID: Trustworthy cloud-based and cross-enterprise biometric identification

2015 ◽  
Vol 42 (21) ◽  
pp. 7905-7916 ◽  
Author(s):  
Mohammad Haghighat ◽  
Saman Zonouz ◽  
Mohamed Abdel-Mottaleb
Keyword(s):  
Biometric Identification

Main Directions of Prevention of Group Offenses among Juvenile Convicts in Young Offender Institutions

2021 ◽  
pp. 87-92
Author(s):  
Konstantin V. Karetnikov ◽  
Keyword(s):  
Electronic Monitoring ◽  
Management Systems ◽  
Biometric Identification ◽  
Young Offender ◽  
Criminal Offense ◽  
Video Cameras ◽  
Penal Institutions ◽  
Control And Management ◽  
Special Category

The federal legislation views the prevention of juvenile delinquency and antisocial actions as very significant, since an offense is understood as an administrative offense and a criminal offense, and antisocial actions include other offenses. This issue is topical for young offender institutions; however, the special category of detainees implies a special category of crimes and violations of the established order of serving the sentence (disciplinary responsibility of convicts). By the end of 2020, there were 949 people in 18 young offender institutions. According to the statistics, the convicts did not commit crimes, yet there were more than 545 other violations. In the current circumstances, it is necessary to improve the prevention of offenses by focusing on specific activities in penal institutions, including active use of non-contact supervision over the behavior of convicts (stationary video cameras, portable video recorders, biometric identification means, access control and management systems). The researchers and practitioners are discussing the possibility of using electronic monitoring systems to supervise the behavior of convicts. This will allow a better quality of supervision over the special contingent and more effective preventive activities in young offender institutions.

ALGORITHMS FOR FINGERPRINT CLASSIFICATION

2021 ◽  
Vol 335 (1) ◽  
pp. 39-44
Author(s):  
D. Lebedev ◽  
A. Abzhalilova
Keyword(s):  
Neural Network ◽  
Gabor Filter ◽  
Recognition System ◽  
Personal Identification ◽  
External Object ◽  
Biometric Identification ◽  
Fingerprint Classification ◽  
Combined Application ◽  
Traditional Approaches

Currently, biometric methods of personality are becoming more and more relevant recognition technology. The advantage of biometric identification systems, in comparison with traditional approaches, lies in the fact that not an external object belonging to a person is identified, but the person himself. The most widespread technology of personal identification by fingerprints, which is based on the uniqueness for each person of the pattern of papillary patterns. In recent years, many algorithms and models have appeared to improve the accuracy of the recognition system. The modern algorithms (methods) for the classification of fingerprints are analyzed. Algorithms for the classification of fingerprint images by the types of fingerprints based on the Gabor filter, wavelet - Haar, Daubechies transforms and multilayer neural network are proposed. Numerical and results of the proposed experiments of algorithms are carried out. It is shown that the use of an algorithm based on the combined application of the Gabor filter, a five-level wavelet-Daubechies transform and a multilayer neural network makes it possible to effectively classify fingerprints.

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