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A Review of Finger-Vein Biometrics Identification Approaches


Affiliations
1 Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
 

Biometrics trait using finger-vein has attracted numerous attention from researchers all over the world since the last decade. Various approaches have been proposed in regard to improving the accuracy of identification result. This paper discusses on the approaches taken from other researches on preprocessing, feature extraction and classification stage specifically for recognizing individual identity. The strengths and weaknesses of these approaches are critically reviewed. The classification approach using machine learning method is highlighted to determine the future direction and to fill the research gap in this field.

Keywords

Biometric, Classification, Feature Extraction, Finger-Vein, Machine Learning, Preprocessing.
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  • A Review of Finger-Vein Biometrics Identification Approaches

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Authors

K. Syazana-Itqan
Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
A. R. Syafeeza
Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
N. M. Saad
Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
Norihan Abdul Hamid
Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia
Wira Hidayat Bin Mohd Saad
Machine Learning and Signal Processing Research Group, Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Malaysia

Abstract


Biometrics trait using finger-vein has attracted numerous attention from researchers all over the world since the last decade. Various approaches have been proposed in regard to improving the accuracy of identification result. This paper discusses on the approaches taken from other researches on preprocessing, feature extraction and classification stage specifically for recognizing individual identity. The strengths and weaknesses of these approaches are critically reviewed. The classification approach using machine learning method is highlighted to determine the future direction and to fill the research gap in this field.

Keywords


Biometric, Classification, Feature Extraction, Finger-Vein, Machine Learning, Preprocessing.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i32%2F128887