Abstract
This paper presents a biometric recognition based on the iris of a human eye using gray-level co-occurrence matrix (GLCM). A new approach of GLCM, called 3D-GLCM, which is expanded from the original 2D-GLCM is proposed and used to extract the iris features. The experimental results show that the proposed approach gains an encouraging performance on the UBIRIS iris database. The recognition rate up to 99.65% can be achieved.
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Miller, B.: Vital Signs of Identity. IEEE Spectrum 31, 22–30 (1994)
Daugman, J.G.: High Confidence Visual Recognition of Persons by a Test of Statistical Independence. IEEE Trans. Pattern Analysis and Machine Intell. 15, 1148–1161 (1993)
Wildes, R.P., et al.: A machine-Vision System for Iris Recognition. Machine Vision and Applications 9, 1–8 (1996)
Boles, W.W., Boashash, B.: A Human Identification Technique using Images of the Iris and Wavelet Transform. IEEE Trans. on Signal Processing 46, 1185–1188 (1998)
Zhu, Y., Tan, T., Wang, Y.: Biometric Personal Identification based on Iris Patterns. In: Proc. of Int. Conf. on Pattern Recognition, vol. II, pp. 801–804 (2000)
Ma, L., Wang, Y., Tan, T.: Iris Recognition using Circular Symmetric Filters. In: Proc. of Int. Conf. on Pattern Recognition, vol. II, pp. 414–417 (2002)
Ma, L., Tan, T., Wang, Y., Zhang, D.: Personal Identification based on Iris Texture Analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 25, 1519–1533 (2003)
Lim, S., Lee, K., Byeon, O., Kim, T.: Efficient Iris Recognition Through Improvement of Feature Vector and Classifier. ETRI Journal 23, 61–70 (2001)
Monro, D., Rakshit, M.S., Zhang, D.: DCT-based Iris Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 29, 586–595 (2007)
Thornton, J., Savvides, M., Vijaya Kumar, B.V.K.: A Bayesian Approach to Deformed Pattern Matching of Iris Images. IEEE Trans. on Pattern Analysis and Machine Intelligence 29, 596–606 (2007)
Haralick, R.M., Shanmugam, K., Dinstein, L.: Textural Features for Image Classification. IEEE Trans. on Systems, Man, and Cybernetics 3, 610–621 (1973)
Valkealahti, K., Oja, E.: Reduced Multidimensional Co-occurrence Histograms in Texture Classification. IEEE Trans. on Pattern Analysis and Machine Intelligence 20, 90–94 (1998)
Zwiggelaar, R.: Texture based Segmentation: Automatic Selection of Co-occurrence Matrices. In: 17th Int. Conf. on Pattern Recognition, vol. 1, pp. 588–591 (2004)
Partio, M., Cramariuc, B., Gabbouj, M., Visa, A.: Rock Texture Retrieval using Gray Level Cco-occurrence Matrix. In: 6th Nordic Signal Processing Symposium, Norway (2002)
Yazdi, M., et al.: Novel Ridge Orientation based Approach for Fingerprint Identification using Co-occurrence Matrix. In: Proc. of World Academy of Science, Engineering and Technology, vol. 26, pp. 371–375 (2007)
Dabbah, M.A., Woo, W.L., Dlay, S.S.: Secure Authentication for Face Recognition. In: Proc. of IEEE Symp. on Comput. Intell. In: Image and Signal Proc., pp. 121–126 (2007)
Busch, A., et al.: Texture for Script Identification. IEEE Trans. on Pattern Analysis and Machine Intelligence 27, 1720–1732 (2005)
Szewczyk, R., et al.: Automatic People Identification on the Basis of Iris Pattern - extraction features and classification. In: Proc. Int. Conf. on Microelectronics, pp. 691–694 (2002)
Gupta, G., Agarwal, M.: Iris Recognition using Non Filter-based Techniques. In: Biometric Consortium Conference (2005)
Bachoo, A.K., Tapamo, J.R.: Texture Analysis and Unsupervised Clustering for Segmenting Iris Images. In: ACM Int. Conf. Proc. Series, vol. 150, pp. 236–243 (2005)
Zaim, A., et al.: A New Method for Iris Recognition using Gray-Level Co-occurrence Matrix. In: IEEE International Conference on Electro/information Technology, pp. 350–353 (2006)
Proenc, H., Alexandre, L.A.: Ubiris Iris Image Database, http://iris.di.ubi.pt
Poursaberi, A., Araabi, B.N.: A Novel Iris Recognition System using Morphological Edge Detector and Wavelet Phase Features. ICGST Int. J. on Graphics, Vision and Image Processing 5, 9–15 (2005)
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Chen, WS., Huang, RH., Hsieh, L. (2009). Iris Recognition Using 3D Co-occurrence Matrix. In: Tistarelli, M., Nixon, M.S. (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_113
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DOI: https://doi.org/10.1007/978-3-642-01793-3_113
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