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A Review on Implementation of Biometric Iris Recognition

Monika Singh1 , Sanjeev Kumar Sharma2

  1. Dept. of Computer Science, Oriental Institute of Science & Technology, Bhopal, India.
  2. Dept. of Computer Science, Oriental Institute of Science & Technology, Bhopal, India.

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 630-635, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.630635

Online published on May 31, 2018

Copyright © Monika Singh, Sanjeev Kumar Sharma . 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: Monika Singh, Sanjeev Kumar Sharma, “A Review on Implementation of Biometric Iris Recognition,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.630-635, 2018.

MLA Style Citation: Monika Singh, Sanjeev Kumar Sharma "A Review on Implementation of Biometric Iris Recognition." International Journal of Computer Sciences and Engineering 6.5 (2018): 630-635.

APA Style Citation: Monika Singh, Sanjeev Kumar Sharma, (2018). A Review on Implementation of Biometric Iris Recognition. International Journal of Computer Sciences and Engineering, 6(5), 630-635.

BibTex Style Citation:
@article{Singh_2018,
author = {Monika Singh, Sanjeev Kumar Sharma},
title = {A Review on Implementation of Biometric Iris Recognition},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {630-635},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2032},
doi = {https://doi.org/10.26438/ijcse/v6i5.630635}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.630635}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2032
TI - A Review on Implementation of Biometric Iris Recognition
T2 - International Journal of Computer Sciences and Engineering
AU - Monika Singh, Sanjeev Kumar Sharma
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 630-635
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

Biometric is considered as an authentic system to recognize a human with respect to their behavior and body features. Automatic verification of features like finger print, palm print, iris recognition is considered a proficient way to grant an access to any system. Among all those, iris is taken as one of the admired technique of recognition which needs precise recognition to execute the whole system. To extract those features which exists in the texture of eye and identify it with the existing database requires various methods to get performed like segmentation, preprocessing, normalization etc. For all those methods, various algorithms have been developed and their effectiveness varies according to the circumstances in which they have been applied. This paper proposes a review on various systems and their developed technique on which researchers have previously worked. Due to several issues, methods which have been developed, till now, can’t consider for wide implementation. So, the system which has been proposed in this paper provides an iris recognition or authentication system using Savitzky-Golay filter for iris feature extraction. A Savitzky–Golay filter is a digital filter that can be applied to a set of digital data points for the purpose of smoothing or enhancing the data without distorting the information. The approach also proves that the symbolic representation effectively handles noise and degradations, including low resolution, specular reflection, and occlusion of eyelids present in the eye images and uses minimum number of features to represent iris image. This system can be implemented in various fields such as banking, security concern areas and many more. Major Canadian Airports have been using Iris recognition systems to expedite passengers through customs.

Key-Words / Index Term

Biometric System, IRIS recognition, Savitzky-Golay Filter, Eye Lids, Feature Extraction

References

[1] Fabián Rolando Jiménez López et al., “Biometric Iris Recognition Using Hough Transform”, IEEE- 2013.
[2] Arezou Banitalebi Dehkordi et al., “Noise Reduction in Iris Recognition Using Multiple Thresholding”, International Conference on Signal and Irnage Processing Applications, IEEE 2013.
[3] P.Thirumurugan et al., “Iris Recognition using Wavelet Transformation Techniques”, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.1, January- 2014.
[4] Navjot Kaur and Mamta Juneja, “A Review on Iris Recognition”, IEEE 2014.
[5] Amena Khatun, A. K. M. Fazlul Haque et al., “Design and Implementation of Iris Recognition Based Attendance Management System”,IEEE 2015.
[6] Mateusz Trokielewicz et al., “Iris Recognition with a Database of Iris Images Obtained in Visible Light Using Smartphone Camera”, IEEE -2016.
[7] Sarika B. Solanke et al., “Biometrics: Iris Recognition System, A Study of Promising Approaches For Secure Authentication”, IEEE 2016.
[8] Jagadeesh N. et al., “Iris recognition system development using Matlab”, International Conference on Computing Methodologies and Communication, IEEE 2017.
[9] tedmontgomery.com/the_eye/iris.html.
[10] github.com/ghazi94/IRIS-Segmentation.
[11] Raghavender ReddyJillela et al. “Segmenting iris images in the visible spectrum with applications in mobile biometrics”, Science Direct, 2014.
[12] Iqra Altaf Mattoo and Parul Agarwal, “Iris Biometric Modality: A Review”, OJCST, 2017.
[13] https://geektimes.ru/post/247634/