Open Access Peer-reviewed

A New Iris Detection Method based on Cascaded Neural Network

Faezeh Mohseni Moghadam1, Azadeh Ahmadi1,, Farshid Keynia2

1Department of Computer Engineering, University of Science and Technology, Kerman,Iran

2Graduate University of Advanced Technology,Kerman,Iran

Journal of Computer Sciences and Applications. 2013, 1(5), 80-84. DOI: 10.12691/jcsa-1-5-1
Published online: August 25, 2017

Abstract

Iris recognition is one of the most reliable and applicable methods for a person's identification. The most complex and important phase of recognition is iris segmentation of an input eye image that affects iris recognition successful rate significantly. Due to missed parameters in noisy images, main error occurs in the performance of classic localization. Artificial neural networks (ANN) are appropriate substitutes for classic methods because of their flexibility on noisy images. In this paper, we use feedforward neural network (FFNN) for the improvement of iris localization accuracy. We apply two methods in order to reduce neural network error: first, designing one neural network for each output neuron .Second, using cascaded feedforward neural network (CFFNN). Then, we examine proposed methods on different datasets which cause remarkable reduction of localization error.

Keywords:

biometric, Iris localization, feedforward neural network, cascaded neural network, daugman's method,neural network designing
[1]  Fadi N.Sibai, Hafsa I.Hosani, Raja M.Naqbi, Salima Dhanhani, Shaikha Shehhi ,"Iris Recognition Using Artificial Neural Networks," Expert Systems With Applications 38,5940-5946,2011.View Article
 
[2]  http://en.wikipedia.org/wiki/Iris_Recognition.
 
[3]  ]http://www.wikipedia.org/wiki/John_Daugman.
 
[4]  Ruggero Donida Labati ,Vincenzo Piuri Fellow, Fabio Scotti,"Neural-based Iterative Approach for Iris Detection in Iris Recognition systems," Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Security and Defense Applications (CISDA ).View Article
 
[5]  K.Saminathan, M.Chithra Devi,T.Chakravarthy "Pair of Iris Recognition for Personal Identification Using Artificial Neural Network," IJCSI International Journal of Computer Science Issues, Vol.9, Issue 1, No.3, January 2012.
 
[6]  Poornima.S,C.Rajavelu, Dr.S.Subramanian," Comparison and Neural Network Approach for Iris Localization," Procedia Computer Science 2,127-132, 2010.View Article
 
[7]  Shivani Godara, Dr.Rajeev Gupta" Comparison of Different Neural Networks for Iris Recognition :A Review," Network and Complex Systems, Vol.2,N0.4,2012.
 
[8]  Zhaofeng He, Tieniu Tan,Fellow, Zhenan Sun, Xianchao," Toward Accurate and Fast Iris Segmentation for Iris Biometrics," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.31, N0.9, September 2009.
 
[9]  Daugman J," How Iris Recognition Works," IEEE Transaction CSV,Vol.14,N0.1,.21-30,2004.
 
[10]  J.Daugman," High Confidence Visual Recognition by a Test of Statistical Independence," IEEE Trans.Pattern Analysis and Machine Intelligence,Vol.15, No.11.1148-1161,1993.
 
[11]  Abdul Basit," Iris Localization Using Grayscale Texture Analysis And Recognition Using Bit Planes", 2009, 16-26.
 
[12]  R.Wildes, J.Asmuth, G.Green, S.Hsu,R.Kolczynski, J.Matey and S.McBride," A Machine Vision System for Iris Recognition," Machine visual Application, Vol.9,. 1-8,1996.
 
[13]  R.Wildes, " Iris Recognition: An Emerging Biometric Technology, "IEEE Proceedings, Vol.85, 1348-1363, 1997.
 
[14]  R.Wildes,”A System For Automated Iris Recognition,” Proceeding of 2nd IEEE Workshop on Applications of Computer Vision, 121-128, 1994.
 
[15]  Li Ma, Tieniu Tan, Yunhong Wang, Dexin Zhang," Personal Identification based on Iris Texture Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.25, No.12, 1519-1533,2003.
 
[16]  ]www.wikipedia.org/wiki/Correlation_and_dependence.
 
[17]  Jain.A.,Ross.A.,& Prabhakar.S," An Introduction to Biometric Recognition," IEEE Transactions on Circuits and System for Video Technology. Special Issue on Image and Video – Based Biometrics,2007.
 
[18]  Libor Masek, “Re1cognition of Human Iris Patterns for Biometric Identification”, School of Computer Science and Sof t Engineering, The University of Western Australia, 2003.
 
[19]  George Bebis, Michael Georgiopoulos" Optimal Feedforward Neural Network Architectures," IEEE Potential separtment of Electrical & Computer Engineering University of Central Florida, Orlando, FL 32816 USA, 2011, 27-3.