Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15607
Title: EAI-NET: Effective and Accurate Iris Segmentation Network
Authors: Rajpal S.
Sadhya D.
De K.
Pratim Roy, Partha
Raman, Balasubramanian
Deka B.
Bhattacharyya D.K.
Maji P.
Mitra S.
Pal S.K.
Bora P.K.
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract: In iris-based biometric models, segmentation of the iris region from the rest of the eye is a crucial step. The quality of the segmented region directly affects the extracted iris features, which subsequently determines the overall recognition accuracy of the model. In this work, we propose EAI-Net, which is an effective and accurate iris segmentation network based on the U-Net architecture. In comparison to the previous works, we treat the segmentation process as a 3-class problem wherein the pupil, iris and the rest of the image are treated as separate classes. Furthermore, we have increased the complexity degree of our model by encoding the complex regions of the iris more efficiently. We have conducted both qualitative and quantitative assessments of our results over four benchmark iris databases - UBIRISv2, IITD, CASIAv4-Interval, and CASIAv4-Thousand. The obtained results demonstrate the superiority of our model over the other state-of-the-art deep-learning based approaches in solving the problem of iris segmentation in both the visible (VIS) and near-infrared (NIR) spectrum. © 2019, Springer Nature Switzerland AG.
Citation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (2019), 442- 451
URI: https://doi.org/10.1007/978-3-030-34869-4_48
http://repository.iitr.ac.in/handle/123456789/15607
Issue Date: 2019
Publisher: Springer
Keywords: Iris
Segmentation
U-Net
ISBN: 9.78E+12
ISSN: 3029743
Author Scopus IDs: 57212452122
56926822500
57204533373
56880478500
23135470700
Author Affiliations: Rajpal, S., Indiana University Bloomington, Bloomington, IN, United States
Sadhya, D., ABV-Indian Institute of Information Technology and Management Gwalior, Gwalior, India
De, K., NTNU Norwegian University of Science and Technology, Gjovik, Norway
Roy, P.P., Indian Institute of Technology Roorkee, Roorkee, India
Raman, B., Indian Institute of Technology Roorkee, Roorkee, India
Corresponding Author: Sadhya, D.; ABV-Indian Institute of Information Technology and Management GwaliorIndia; email: debanjan@iiitm.ac.in
Appears in Collections:Conference Publications [CS]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.