Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46949
Title: A new wrist vein biometric system
Authors: Das, Abhijit
Pal, Umapada
Ballester, Miguel Angel Ferrer 
Blumenstein, Michael
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Veins
Wrist
Feature extraction
Adaptive equalizers
Support vector machines
Issue Date: 2015
Journal: IEEE Workshop on Computational Intelligence in Biometrics and Identity Management, CIBIM
Conference: 2014 IEEE Symposium Series on Computational Intelligence, IEEE SSCI 2014 - 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, CIBIM 2014 
Abstract: In this piece of work a wrist vein pattern recognition and verification system is proposed. Here the wrist vein images from the PUT database were used, which were acquired in visible spectrum. The vein image only highlights the vein pattern area so, segmentation was not required. Since the wrist's veins are not prominent, image enhancement was performed. An Adaptive Histogram Equalization and Discrete Meyer Wavelet were used to enhance the vessel patterns. For feature extraction, the vein pattern is characterized with Dense Local Binary Pattern (D-LBP). D-LBP patch descriptors of each training image are used to form a bag of features, which was used to produce the training model. Support Vector Machines (SVMs) were used for classification. An encouraging Equal Error Rate (EER) of 0.79% was achieved in our experiments.
URI: http://hdl.handle.net/10553/46949
ISBN: 9781479945344
ISSN: 2325-4300
DOI: 10.1109/CIBIM.2014.7015445
Source: IEEE Workshop on Computational Intelligence in Biometrics and Identity Management, CIBIM[ISSN 2325-4300],v. 2015-January (7015445), p. 68-75
Appears in Collections:Actas de congresos
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