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Liveness Detection of a Hand
 Vanický, Jozef ; Kanich, Ondřej (oponent) ; Sakin, Martin (vedoucí práce)
This thesis solves the security problem of biometric systems which uses biometric data of a hand. It focuses on the absence of liveness detection during verification of a sample by the biometric system. In result this thesis offers to extend the contactless biometric systems by a system of liveness detection, which utilizes specific properties of human skin and its reactions to certain wavelengths of the visible spectrum of electromagnetic radiation. Reactions of the skin on the specific wavelengths of visible spectrum are analyzed and compared with the reactions of inorganic materials which imitates the hand. Outcome of this thesis is a design and implementation of a liveness detection algorithm, which can, based on the analysis of a set of photographs of the human palm, which was exposed to four wavelengths of a visible part of the electromagnetic spectrum, successfully recognize a hand from a counterfeit with an average accuracy rate of 82.20 %.
Úplný záznam
Liveness Detection of a Hand
 Vanický, Jozef ; Kanich, Ondřej (oponent) ; Sakin, Martin (vedoucí práce)
This thesis solves the security problem of biometric systems which uses biometric data of a hand. It focuses on the absence of liveness detection during verification of a sample by the biometric system. In result this thesis offers to extend the contactless biometric systems by a system of liveness detection, which utilizes specific properties of human skin and its reactions to certain wavelengths of the visible spectrum of electromagnetic radiation. Reactions of the skin on the specific wavelengths of visible spectrum are analyzed and compared with the reactions of inorganic materials which imitates the hand. Outcome of this thesis is a design and implementation of a liveness detection algorithm, which can, based on the analysis of a set of photographs of the human palm, which was exposed to four wavelengths of a visible part of the electromagnetic spectrum, successfully recognize a hand from a counterfeit with an average accuracy rate of 82.20 %.
Úplný záznam

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