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Inner Iris Localization and Statistical Feature Extraction of CASIA and KVKR Databases

Published on August 2016 by Yogesh M. Rajput, Ramesh R. Manza, Karbhari V. Kale
journal_cover_thumbnail

National Conference on Digital Image and Signal Processing
Foundation of Computer Science USA
NCDISP2016 - Number 1
August 2016
Authors: Yogesh M. Rajput, Ramesh R. Manza, Karbhari V. Kale
8fb9d14f-e454-4e80-b729-809be2de96b8

Yogesh M. Rajput, Ramesh R. Manza, Karbhari V. Kale . Inner Iris Localization and Statistical Feature Extraction of CASIA and KVKR Databases. National Conference on Digital Image and Signal Processing. NCDISP2016, 1 (August 2016), 6-9.

@article{
author = { Yogesh M. Rajput, Ramesh R. Manza, Karbhari V. Kale },
title = { Inner Iris Localization and Statistical Feature Extraction of CASIA and KVKR Databases },
journal = { National Conference on Digital Image and Signal Processing },
issue_date = { August 2016 },
volume = { NCDISP2016 },
number = { 1 },
month = { August },
year = { 2016 },
issn = 0975-8887,
pages = { 6-9 },
numpages = 4,
url = { /proceedings/ncdisp2016/number1/25846-1623/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Digital Image and Signal Processing
%A Yogesh M. Rajput
%A Ramesh R. Manza
%A Karbhari V. Kale
%T Inner Iris Localization and Statistical Feature Extraction of CASIA and KVKR Databases
%J National Conference on Digital Image and Signal Processing
%@ 0975-8887
%V NCDISP2016
%N 1
%P 6-9
%D 2016
%I International Journal of Computer Applications
Abstract

A new system for personal identification based on inner iris localization and calculate statistical features is presented in this paper. It is collected of iris image acquisition, image preprocessing and statistical feature extraction. The algorithm for iris feature extraction is based on digital image processing techniques. This algorithm is tested on CASIA iris image database, which is online available and local database collected from KVKR research lab.

References
  1. http://biometrics. idealtest. org/dbDetailForUser. do?id=4. (CASIA)
  2. R. Kevin, ?E-Security for E-Government? A Kyberpass Technical White Paper, April 2001, www. kyberpass. com.
  3. John Daugman,?How Iris works? IEEE Transaction on circuit and systems for Video Technology, VOL. 14, No. 1, January 2004.
  4. D. Zang Automated biometrics technologies and systems Klumer Academics, Boston, Mass, USA, 2000.
  5. "Understanding MATLAB" By Karbhari Kale, Ramesh R. Manza, Ganesh R. Manza, Vikas T. Humbe, Pravin L. Yannawar, Shroff Publisher & Distributer Pvt. Ltd. , Navi Mumbai, April 2013. ISBN: 9789350237199.
  6. "Understanding GUI using MATLAB for Students" By Ramesh Manza, Manjiri Patwari & Yogesh Rajput, Shroff Publisher & Distributer Pvt. Ltd. , Navi Mumbai, April 2013. ISBN: 9789351109259.
  7. Kavita Khobragade & K. V. Kale, "Iris Edge Detection with Bit-Plane Slicing Technique", IJCA Proceedings on National Conference on Recent Advances in Information Technology, (0975 – 8887) 2014.
  8. Kavita Khobragade, Dr. K. V. Kale, "An Iris Localization Algorithm : A Review", International Journal of Advances in Management, Technology & Engineering Sciences (IJAMTES], Vol. 1, Issue 6 (IX), March 2012, pp- 194-197, ISSN : 2249-7455
  9. Kavita Khobragade, "Study and Comparison of Iris Edge Detection Technique", Online Peer Review International Journal of Computer Architecture and Mobility, [ISSN: 2319-9229], Volume 1, Issue 5, March 2013.
  10. Kavita Khobragade, Dr. K. V. Kale, "A New Technique for Fast and Accurate Iris Localization", Online Peer Review International Journal of Innovations in Engineering and Technology, (IJIET), Volume 3, Issue 3, February 2014, pp-25-32, [ISSN: 2319-1058].
Index Terms

Computer Science
Information Sciences

Keywords

Iris Localization Statistical Features