2018
Vasilopoulos, Christos; Skodras, Athanassios
A Novel Finger Vein Recognition System Based on Enhanced Maximum Curvature Points Proceedings Article
In: 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), pp. 1-5, 2018.
Abstract | Links | BibTeX | Tags: biometrics, Enhanced Maximum Curvature Points, feature extraction, finger vein recognition, Personal identification
@inproceedings{Vasilopoulos2018,
title = {A Novel Finger Vein Recognition System Based on Enhanced Maximum Curvature Points},
author = {Christos Vasilopoulos and Athanassios Skodras},
doi = {10.1109/IVMSPW.2018.8448746},
year = {2018},
date = {2018-06-01},
booktitle = {2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)},
pages = {1-5},
abstract = {Finger vein recognition is a biometric method of authentication that offers high security, efficiency and stability. In this paper we propose a new finger vein recognition system that utilizes the Enhanced Maximum Curvature Points (EMC) technique for finger vein pattern extraction and introduces a new pre-processing stage. In addition, it combines two matching methods, leading to better recognition performance in terms of EER, FAR, FRR and recognition rate than other methods. We present the experimental results obtained by applying our system on the databases SDUMLA-HMT, Tsingua, FV-USM and HKPU and compare them with similar approaches applied on these databases.},
keywords = {biometrics, Enhanced Maximum Curvature Points, feature extraction, finger vein recognition, Personal identification},
pubstate = {published},
tppubtype = {inproceedings}
}
2017
Tagkalakis, Fotios; Vlachakis, Dimitrios; Megalooikonomou, Vasileios; Skodras, Athanassios
A novel approach to finger vein authentication Proceedings Article
In: 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 659-662, 2017, ISSN: 1945-8452.
Abstract | Links | BibTeX | Tags: bio-identity, biometrics, digital signatures, finger vein authentication, person identification
@inproceedings{Tagkalakis2017,
title = {A novel approach to finger vein authentication},
author = {Fotios Tagkalakis and Dimitrios Vlachakis and Vasileios Megalooikonomou and Athanassios Skodras},
doi = {10.1109/ISBI.2017.7950606},
issn = {1945-8452},
year = {2017},
date = {2017-04-01},
booktitle = {2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)},
pages = {659-662},
abstract = {Finger vein patterns are unique biometric features, which differentiate from individual to individual, so they are suitable for authentication applications. Systems based on the use of this feature have numerous advantages such as low cost and high accuracy. A new finger vein authentication approach is proposed, which is based on the efficient detection of the non-vein regions, in order to define the main vein patterns. The proposed method is robust in extracting and depicting not only the finger's vein pattern, but also other important features such as the veins' width. The authentication algorithm has been evaluated on a finger vein database of 400 images. The false acceptance and false rejection rates achieved are 0% and 0.5% respectively.},
keywords = {bio-identity, biometrics, digital signatures, finger vein authentication, person identification},
pubstate = {published},
tppubtype = {inproceedings}
}