Iris Recognition Based on Using Ridgelet and Curvelet Transform

Biometric methods have been played important roles in personal recognition during last twenty years. These methods include the face recognition, finger print and iris recognition. Recently iris imaging has many applications in security systems. The aim of this paper is to design and implement a new iris recognition algorithm. In this paper, the new feature extraction methods according to ridgelet transform and curvelet transform for identifying the iris images are provided. At first, after segmentation and normalization the collarette area of iris images has been extracted. Then we improve the quality of image by using median filter, histogram equalization, and the two-dimensional (2D) Wiener filter as well. Finally the ridgelet transform and curvelet transform are applied for extracting features and then the binary bit stream vectors are generated. The Hamming distance (HD) between the input bit stream vector and stored vectors is calculated for iris identification. The experimental results show efficiency of our proposed method.

[1]  Yillbyung Lee,et al.  Iris recognition using collarette boundary localization , 2004, ICPR 2004.

[2]  Andrew Beng Jin Teoh,et al.  Iris Authentication Using Privatized Advanced Correlation Filter , 2006, ICB.

[3]  A. Zaim,et al.  A New Method for Iris Recognition using Gray-Level Coccurence Matrix , 2006, 2006 IEEE International Conference on Electro/Information Technology.

[4]  Boualem Boashash,et al.  A human identification technique using images of the iris and wavelet transform , 1998, IEEE Trans. Signal Process..

[5]  B. V. K. Vijaya Kumar,et al.  Iris Verification Using Correlation Filters , 2003, AVBPA.

[6]  Hamid Reza Pourreza,et al.  Efficient IRIS Recognition through Improvement of Feature Extraction and subset Selection , 2009, ArXiv.

[7]  Emmanuel J. Candès,et al.  The curvelet transform for image denoising , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Okhwan Byeon,et al.  Efficient Iris Recognition through Improvement of Feature Vector and Classifier , 2001 .

[11]  Hao Meng,et al.  Iris Recognition Algorithms Based on Gabor Wavelet Transforms , 2006, 2006 International Conference on Mechatronics and Automation.

[12]  Kang Ryoung Park,et al.  Iris Recognition in Mobile Phone Based on Adaptive Gabor Filter , 2006, ICB.

[13]  Mayank Vatsa,et al.  Reducing the False Rejection Rate of Iris Recognition Using Textural and Topological Features , 2008 .

[14]  Yong Haur Tay,et al.  An effective segmentation method for iris recognition system , 2008 .

[15]  Agus Harjoko,et al.  A Method for Iris Recognition Based on 1D Coiflet Wavelet , 2009 .

[16]  Pengfei Shi,et al.  A new segmentation approach for iris recognition based on hand-held capture device , 2007, Pattern Recognit..

[17]  Vladan Velisavljevic,et al.  Low-Complexity Iris Coding and Recognition Based on Directionlets , 2009, IEEE Transactions on Information Forensics and Security.

[18]  Kang Ryoung Park,et al.  Fake Iris Detection by Using Purkinje Image , 2006, ICB.

[19]  A. Basit,et al.  Iris Recognition Using Wavelet , 2007, 2007 International Conference on Emerging Technologies.

[20]  Md. Selim Al Mamun,et al.  Iris recognition: A new approach for iris segmentation , 2009, C3IT 2009.

[21]  Vladan Velisavljevic.  Low-complexity iris recognitionwith orientedwavelets , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[22]  Emmanuel J. Candès,et al.  The curvelet transform for image denoising , 2002, IEEE Trans. Image Process..

[23]  John Daugman,et al.  High Confidence Visual Recognition of Persons by a Test of Statistical Independence , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Pengfei Shi,et al.  An Efficient Iris Segmentation Method for Recognition , 2005, ICAPR.

[25]  R.W. Ives,et al.  Iris recognition using histogram analysis , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[26]  T. Tan,et al.  Iris Recognition Based on Multichannel Gabor Filtering , 2002 .