Paper Info
Title
A Texture-Based Neural Network Classifier for Biometric Identification using Ocular Surface Vasculature
Abstract
In an earlier work we had explored the possibility of utilizing the vascular pattern of the sclera, episclera, and conjunctiva as a biometric indicator. These blood vessels, which can be observed on the white part of the human eye, demonstrate rich and seemingly unique details in visible light, and can be easily imaged using commercially available digital cameras. In this work we discuss a new method to represent and match the textural intricacies of this vascular structure using wavelet-derived features in conjunction with neural network classifiers. Our experimental results, based on the evidence of 50 subjects, indicate the potential of the proposed scheme to characterize the individuality of the ocular surface vascular patterns and further confirm our assertion that these patterns are indeed unique across individuals.
Year
DOI
Venue
2007
10.1109/IJCNN.2007.4371435
Orlando, FL
Keywords
Field
DocType
biometrics (access control),image texture,neural nets,wavelet transforms,biometric identification,ocular surface vasculature,texture-based neural network classifier,wavelet-derived feature
Human eye,Computer vision,Pattern recognition,Neural network classifier,Computer science,Image texture,Vascular structure,Sclera,Artificial intelligence,Biometrics,Artificial neural network,Wavelet transform
Conference
ISSN
ISBN
Citations 
1098-7576 E-ISBN : 978-1-4244-1380-5
978-1-4244-1380-5
23
PageRank 
References 
Authors
1.12
9
2
Name
Order
Citations
PageRank
Reza Derakhshani116621.08
Arun Ross23096177.30