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State-of-the art iris segmentation methods: A Survey

R. Satish1 , P. Rajesh Kumar2

Section:Survey Paper, Product Type: Journal Paper
Volume-6 , Issue-11 , Page no. 739-748, Nov-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i11.739748

Online published on Nov 30, 2018

Copyright © R. Satish, P. Rajesh Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R. Satish, P. Rajesh Kumar, “State-of-the art iris segmentation methods: A Survey,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.739-748, 2018.

MLA Style Citation: R. Satish, P. Rajesh Kumar "State-of-the art iris segmentation methods: A Survey." International Journal of Computer Sciences and Engineering 6.11 (2018): 739-748.

APA Style Citation: R. Satish, P. Rajesh Kumar, (2018). State-of-the art iris segmentation methods: A Survey. International Journal of Computer Sciences and Engineering, 6(11), 739-748.

BibTex Style Citation:
@article{Satish_2018,
author = {R. Satish, P. Rajesh Kumar},
title = {State-of-the art iris segmentation methods: A Survey},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2018},
volume = {6},
Issue = {11},
month = {11},
year = {2018},
issn = {2347-2693},
pages = {739-748},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3236},
doi = {https://doi.org/10.26438/ijcse/v6i11.739748}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i11.739748}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3236
TI - State-of-the art iris segmentation methods: A Survey
T2 - International Journal of Computer Sciences and Engineering
AU - R. Satish, P. Rajesh Kumar
PY - 2018
DA - 2018/11/30
PB - IJCSE, Indore, INDIA
SP - 739-748
IS - 11
VL - 6
SN - 2347-2693
ER -

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Abstract

In today’s world scenario where security and privacy are the primary concern, the systems that are developed must employ accurate techniques to achieve this. The biometric recognition provides automated verification of individuals based on unique characteristics processed by an individual. The commercial biometric systems are popular and are used extensively, but not restricted to, in the fields of banking services, access secured database, airport surveillance, access control in the boarders etc. Biometric systems are developed based on the physical or behavioural unique characteristics of the individuals. Iris recognition system is the most reliable and accurate, which is grabbing the attention of the researchers now a day. The iris epigenetic patterns are unique, stable and accurate when compared with the other biometric traits. The iris recognition system is a very good research topic in the areas digital image processing, computer vision & pattern recognition. The segmentation or localization is a very crucial stage, because the system’s accuracy highly relies on segmentation. In this paper, detailed state-of-the-art segmentation techniques have been presented.

Key-Words / Index Term

Iris segmentation, Biometrics, Recognition system, Computer vision

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