Open Access Open Access  Restricted Access Subscription or Fee Access

Iris Recognition System using Ridge Energy Direction

Mayuri M. Memane, Sanjay R. Ganorkar

Abstract


The first and most popular iris recognition algorithm
was introduced by pioneer Dr. J. Daugman which is not available for open use, so an alternative for research purposes can be found in the implementation created by Ives et al. to perform iris recognition, referred as Ridge Energy Direction (RED) algorithm that will be the focus of this work. The first step is to collect the database of iris, than
carry out the various preprocessing steps which includes conversion of color image to gray scale image, histogram equalization, intensity adjustment and segmentation i.e. separation of pupil from the image and select the area of interest. Features are extracted from the area of interest using two directional filters (i.e. vertically and horizontally oriented) which generates two individual templates. The final template is generated by comparing the results of two different directional filters and writing a single bit that represents the filter with the highest output at the equivalent location. This final template is compared with
the stored one using Hamming distance. If the template is match with the stored one than the match ID number of the person is displayed and non-match image is indicated by displaying zero.


Keywords


Biometrics, Iris Recognition, Hamming Distance, Histogram, RED Algorithm, Segmentation.

Full Text:

PDF

References


G. Annapoorani, R. Krishnamoorthi, P. G. Jeya, and S. Petchiammal,

“Accurate and Fast Iris Segmentation,” Int. J. of Engineering Science and

Technology, vol.2, pp.1492-1499, 2010.

J. Daugman, “How iris recognition works,” IEEE Trans on Circuits and

System for Video Technology, vol.14, no.1, pp. 21-30, 2004.

H. A. Hashish, M. S. El-Azab, M. E. Fahmy, M. A. Mohamed, “A

Mathematical Model for Verification of Iris Uniqueness,” Int. J. on

Computer Science and Network Security, vol. 10, pp.146-152, June-2010

R. W. Ives, A. J. Guidry and D. M. Etter, “Iris Recognition using

Histogram Analysis,” in Proc. Conf. Rec.38th Asilomar Conf. Signal,

Systems and Computers, pp.562-566, 2004.

R. W. Ives, R. P. Broussard, L. R. Kennell, R. N. Rakvic and D. M. Etter,

“Iris Recognition using the Ridge Energy Direction (RED) Algorithm,” in

Proc. Conf. Rec. 42nd Asilomar Conf. Signal, Systems and Computers,

Pacific Grove, CA, Nov 2008.

G. Kaur, A. Girdhar, M. Kaur, “Enhanced Iris Recognition System- an

Integrated Approach to Person Identification,” Int. J. of Computer

Applications vol.8, no-1, pp.1-5, Oct. 2010.

Hugo Proenc¸ and Lu´ıs A. Alexandre. “UBIRIS: A noisy iris image data

base,” In Proceedings of the 13th International Conference on Image

Analysis and Processing (ICIAP2005), pp. 970–977, Sep. 2005.

R. N. Rakvic, B. J. Ulis, R. P. Broussard, and R. W. Ives, “Iris template

generation with parallel logic,” in Proc. 42nd Ann. Asilomar Conf.

Signals, Systems and Computers, Pacific Grove, CA, Nov. 2008.

R. N. Rakvic, B. J. Ulis, R. P. Broussard, R. W. Ives and N. Steiner,

“Parallelizing iris recognition,” Trans. Info. For. Sec. Dec 2009

GR. P. Wildes, “Iris Recognition: An Emerging Biometric Technology,”

proceeding of IEEE, vol.85, no.9, pp. 1348-1363, Sep. 1997.

http://www.bobpowell.net/grayscale.htm.

http://en.wikipedia.org/wiki/Histogram_equalization.

http://math.uci.edu/icamp/courses/math77c/demos/hist_eq.pdf.

http://en.wikipedia.org/wiki/Canny_edge_detector.

http://csjournals.com/IJCSC/PDF2-1/Article_43.pdf.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.