Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/51803

TítuloThe Finger-Knuckle-Print recognition using the kernel principal components analysis and the support vector machines
Autor(es)Khellat-Kihel, S.
Abrishambaf, R.
Cabral, Jorge
Monteiro, João L.
Benyettou, M.
Palavras-chaveFinger-Knuckle-Print
SVM
Kernel principal components analysis
Recognition
Data2016
EditoraSpringer
RevistaLecture Notes in Networks and Systems
Resumo(s)In the computer networks explosion's time, the need to identify individuals increasingly becomes necessary to perform various operations, such as access control and secure payments. So far, inputting alphanumeric code remains the most used solution. This solution, in spite of having the merit to be very simple, has the disadvantage to certify only the individual who enters the correct code. Another possibility that is open to us is to use biometric identification, by identifying directly the physical traits of the user. Biometric identification is defined as a science allowing the identification of people using their behavioral or physiologic characteristics. It seems like an evident solution to the problem explained previously: the identity of a person is then related to who he/she is and not to what he/she possesses or knows. In this work, we propose a biometric system based on a very recent biometric trait, which consists in the finger-Knuckle-Prints. This recognition is based on a mathematical model.
TipoconferencePaper
URIhttp://hdl.handle.net/1822/51803
ISBN9783319334097
DOI10.1007/978-3-319-33410-3_13
ISSN2367-3370
Arbitragem científicayes
AcessorestrictedAccess
Aparece nas coleções:CAlg - Livros e capítulos de livros/Books and book chapters

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