Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46948
Title: A new efficient and adaptive sclera recognition system
Authors: Das, Abhijit
Pal, Umapada
Ballester, Miguel Angel Ferrer 
Blumenstein, Michael
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Iris recognition
Image segmentation
Feature extraction
Adaptive systems
Issue Date: 2015
Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 
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 paper an efficient and adaptive biometric sclera recognition and verification system is proposed. Sclera segmentation was performed by Fuzzy C-means clustering. Since the sclera vessels are not prominent, in order to make them clearly visible image enhancement was required. Adaptive histogram equalization, followed by a bank of Discrete Meyer Wavelet was used to enhance the sclera vessel patterns. Feature extraction was performed by, Dense Local Directional Pattern (D-LDP). D-LDP patch descriptors of each training image are used to form a bag of features; further Spatial Pyramid Matching was used to produce the final training model. Support Vector Machines (SVMs) are used for classification. The UBIRIS version 1 dataset was used here for experimentation of the proposed system. To investigate regarding sclera patterns adaptively with respect to change in environmental condition, population, data accruing technique and time span two different session of the mention dataset are utilized. The images in two sessions are different in acquiring technique, representation, number of individual and they were captured in a gap of two weeks. An encouraging Equal Error Rate (EER) of 3.95% was achieved in the above mention investigation.
URI: http://hdl.handle.net/10553/46948
ISBN: 9781479945344
ISSN: 2325-4300
DOI: 10.1109/CIBIM.2014.7015436
Source: IEEE Workshop on Computational Intelligence in Biometrics and Identity Management, CIBIM[ISSN 2325-4300],v. 2015-January (7015436), p. 1-8
Appears in Collections:Actas de congresos
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