Published In : IJCSN Journal Volume 5, Issue 5

Date of Publication : October 2016

Pages : 842-853

Figures :17

Tables :11

 

Rangaswamy Y : is a Assistant Professor in the Department of Electronics and communication Engineering, Alpha college of Engineering, Bangalore. He obtained his B.E. degree in Electronics and Communication Engineering from VTU University and Master degree in Electronics and Communication from University Visvesvaraya college of Engineering, Bangalore University and currently pursuing Ph.D. Under Jawaharlal Nehru Technological University, Anantapur, in the area of Image Processing under the guidance of Dr. K. B. Raja, Professor, Department of Electronics and Communication Engineering, University Visvesvaraya college of Engineering, Bangalore. His area of interest is in the field of Signal and Image Processing and Communication Engineering.

Dr. K B Raja : is a Professor, Department of Electronics and Communication Engineering, University Visvesvaraya college of Engineering (UVCE), Bangalore University, Bangalore. He obtained his BE and ME in Electronics and Communication Engineering from University Visvesvaraya College of Engineering, Bangalore. He was awarded Ph.D. in Computer Science and Engineering from Bangalore University. He has 170 research publications in refereed International Journals and Conference Proceedings. His research interests include Image Processing, Biometrics, and VLSI Signal Processing.

 

 

 

 

 

 

 

Biometrics, Gabor filter, Iris Template, AHE, HE.

Iris biometric trait is used in high security areas to identify a person. In this paper Iris Recognition based on Transformation of Iris Template, AHE, HE and Gabor Wavelet Filter is proposed. The iris template is created using localization and segmentation techniques. The many templates of a person in a database are converted into single person using averaging technique to reduce number of templates per person to increase speed of identification. The AHE and HE are used to enhance quality of iris template. The features are extracted using gabor wavelet filters. The ED is used to compare test and database features to test performance of the proposed algorithm. It is observed that the performance of proposed method is better compared to existing methods.

 

[1] J. Daugman, “How Iris Recognition Works,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, pp.21-30, 2004. [2] R P Wildes, “Iris Recognition: An Emerging Biometric Technology,” IEEE Proceedings, Vol. 85, no 9, pp. 1348-1363, 1997. [3] W W Boles and B Boashash, “A Human Identification Technique using Images of the Iris and Wavelet Transform,” IEEE Transactions on Signal Processing, Vol. 46, No. 4, pp. 1185-1187, 1998. [4] Li Ma, Tieniu Tan, Yunhong Wang and Dexin Zhang, “Personal Identification based on Iris Texture Analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.25, No.12, pp.1519 – 1533, 2003. [5] Vineet Kumar , Abhijit Asati and Anu Gupta “Iris localization based on Integro-Differential Operator for Unconstrained Infrared Iris Images,” IEEE International Conference on Signal Processing, Computing and Control, PP-277-281, 2015. [6] Volnei da S. Klehm ,Wheidima C. Melo ; Felipe S. Farias ; Kenny V. Santos and S. S. Waldir “ Iris Recognition using Minimum Average Correlation Energy and Principal Component,” IEEE Global Conference on Consumer Electronics. pp 213-214, 2015. [7] Arezou Banitalebi Dehkordi Syed A. R. and Abu- Bakar, “Noise Reduction for Iris Recognition using Adaptive Fuzzy Filtering,” IEEE International Conference on Signal and Image Processing Applications, pp 399-403, 2015. [8] Kiran B. Raja, R. Raghavendra and Christoph Busch , “Iris Imaging in Visible Spectrum using White LED,” IEEE International Conference on Biometrics Theory, Applications and systems, pp 1-8, 2015. [9] Nalla Srilatha and C. Krishna Mohan “Sparsity- Based Iris Classification Using Iris Fiber Structures,” International Conference of the Biometrics Special Interest Group , pp 1-4, 2015. [10] Sheetal Chaudhary and Rajender Nath “A New Template Protection Approach for Iris Recognition,” International Conference on Reliability, Infocom Technologies and Optimization, pp 1-6, 2015. [11] Yang Hu Konstantinos Sirlantzis and Gareth Howells , “Signal-Level Information Fusion for Less Constrained Iris Recognition Using Sparse-Error Low Rank Matrix Factorization,” IEEE Transactions on Information Forensics and Security, vol 11, no-7, pp 1549-1564, 2016. [12] Mohammed A. M. Abdullah Satnam S. Dlay ; Wai L. Woo and Jonathon A. Chambers “Robust Iris Segmentation Method Based on a New Active Contour Force With a Noncircular Normalization, IEEE Transactions on Systems, Man, and Cybernetics: vol 14, no-99, pp 1-14, 2016. [13] Yong Zhang and Yan Wo , “A Fusion Iris Feature Extraction based on Fisher Linear Discriminant Method,” IEEE International Conference on Machine Learning and Cybernetics, pp 5-9, 2013. [14] Bashirul Azam Biswas, Shams Shad Islam Khan and S M Mahbubur Rahman, “Discriminative Masking for Non-Cooperative Iriscode Recognition,” IEEE International Conference on Electrical and Computer Engineering, pp 124-127, 2014. [15] Khalid A. Darabkh . Raed T. Al-Zubi and Mariam T. Jaludi, “New Recognition Methods for Human Iris Patterns,” IEEE International Convention on Information and ommunication Technology, Electronics and Microelectronics pp 1187-1191,2014. [16] Tanvir Zaman Khan, Prajoy Podder and Md. Foisal Hossain, “Fast and Efficient Iris Segmentation Approach based on Morphology and Geometry Operation,” IEEE International Conference on Software, Knowledge, Information Management and Applications , pp 1-8,2014 . [17] http://www.sinobiometrics.com, CASIA Iris Image Database. [18] Shashi Kumar D R, K B Raja, R K Chhootaray and Sabyasachi Pattnaik, “PCA based Iris Recognition using DWT,” International Journal Computer Technology and Applications, vol. 2, no. 4, pp. 884- 893, 2011. [19] http://www.springerimages.com,Springer Analysis of CASIA Database. [20] Stephen M. Pizer, E. Philip Amburn, John D. Austin, Robert Cromartie, Ari Geselowitz, TreyGreer, Bart ter Haar Romeny, John B. Zimmerman and Karel Zuiderveld, “Adaptive Histogram Equalization and Its Variations,” Computer Vision, Graphics and Image Processing 39, pp 355-368,1987. [21] Rafael C. Gonzalez and Richard E. Woods Digital Image Processing, Prentice Hall, Second Edition, 2002. [22] Struc V and Pavesic , “Gabor-Based Kernel Partial Least-Squares Discrimination Features for Face Recognition ,” Informatica, vol.20 no. 1, pp.115– 138, 2009. [23] M. Haghighat, S. Zonouz and M. Abd Mottaleb, “Identification Using Encrypted Biometrics,” Computer Analysis of Images and Patterns, Springer Berlin Heidelberg, vol.8048, pp.440–448, 2013. [24] Yang Hu, Konstantinos Sirlantzis and Gareth Howells, Optimal Generation of Iris Codes for Iris Recognition, IEEE Transactions on Information Forensics and Security vol. 1, no.99 ,pp, 1-14, 2016. [25] JianxuChen; FengShen; Danny Ziy iChen; Patrick J. Flynn, “Iris Recognition Based on Human Interpretable Features,” IEEE Transactions on Information Forensics and Security, vol .11 no.7 , pp, 1476-1485, 2016. [26] Sushilkumar, “Iris recognition using SVM and ANN,” IEEE International Conference on Wireless ommunications, Signal Processing and Networking, pp, 474-478, 2016. [27] Nishanth Rao P R, Manoj Hebbar and Manikantan K, “Feature selection using Dynamic Binary Particle Swarm Optimization for enhanced Iris Recognition,” International Conference on Signal Processing and Integrated Networks, pp, 139-146, 2016.