Paper Info
Title
Variation In Accuracy Of Textured Contact Lens Detection Based On Sensor And Lens Pattern
Abstract
Automatic detection of textured contact lenses in images acquired for iris recognition has been studied by several researchers. However, to date, the experimental results in this area have all been based on the same manufacturer of contact lenses being represented in both the training data and the test data and only one previous work has considered images from more than one iris sensor. Experimental results in this work show that accuracy of textured lens detection can drop dramatically when tested on a manufacturer of lenses not seen in the training data, or when the iris sensor in use varies between the training and test data. These results suggest that the development of a frilly general approach to textured lens detection is a problem that still requires attention.
Year
Venue
Keywords
2013
2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS)
image texture,iris recognition,image sensors,lenses
Field
DocType
Citations 
Training set,Iris recognition,Computer vision,Image sensor,Computer science,Image texture,Contact lens,Lens (optics),Test data,Artificial intelligence
Conference
10
PageRank 
References 
Authors
0.57
10
3
Name
Order
Citations
PageRank
James S. Doyle Jr.1684.14
Kevin W. Bowyer211121734.33
Patrick J. Flynn34405307.04