Authors
Ramachandra Raghavendra, Kiran B Raja, Christoph Busch
Publication date
2017/3/24
Conference
2017 IEEE Winter Conference on Applications of Computer Vision (WACV)
Pages
1160-1167
Publisher
IEEE
Description
Contact lens detection in the eye is a significant task to improve the reliability of iris recognition systems. A contact lens overlays the iris region and prevents the iris sensor from capturing the normal iris region. In this paper, we present a novel scheme for detection to detecting a contact lens using Deep Convolutional Neural Network (CNN). The proposed CNN architecture ContlensNet is structured to have fifteen layers and configured for the three-class detection problem with the following classes: images with textured (or colored) contact lens, soft (or transparent) contact lens, and no contact lens. The proposed ContlensNet is trained using numerous iris image patches and the problem of overfitting the network is addressed by using the dropout regularization method. Extensive experiments are carried out on two publicly available large-scale databases, namely: IIIT-Delhi Contact lens iris database (IIITD) and Notre …
Total citations
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Scholar articles
R Raghavendra, KB Raja, C Busch - 2017 IEEE Winter Conference on Applications of …, 2017