[[1] Gulmire, K. and Ganorkar,S., Iris recognition using Gabor wavelet., International Journal of Engineering, 1(5), 2012.]Search in Google Scholar
[[2] Masek, L.: Recognition of human iris patterns for biometric identification. PhD thesis.]Search in Google Scholar
[[3] Ma, L., Tan, T., Wang, Y. and Zhang, D.,:Personal identification based on iris texture analysis., Pattern Analysis and Machine Intelligence, IEEE Transactions on, 25(12):1519- 1533, 2003.]Search in Google Scholar
[[4] Daugman, J.:How iris recognition works., Circuits and Systems for Video Technology, IEEE Transactions on, 14(1):21-30, 2004.10.1109/TCSVT.2003.818350]Search in Google Scholar
[[5] Fatukasi,O., Kittler, J., and Poh, N., :Quality controlled multi-modal fusion of biometric experts., In Progress in Pattern Recognition, Image Analysis and Applications, pages 881-890. Springer, 2007.10.1007/978-3-540-76725-1_91]Search in Google Scholar
[[6] Kalka,N. D., Dorairaj, V.,Shah,Y. N., Schmid, N. A. and Cukic B.,: Image quality assessment for iris biometric., In Proceedings of the 24th Annual Meeting of the Gesellscha it Klassikation, pages 445-452. Springer, 2002.]Search in Google Scholar
[[7] Sandre, S-L and Stevens, M. and Mappes, J.,: The effect of predator appetite, prey warning coloration and luminance on predator foraging decisions, Behaviour, vol.147, No. 9., 1121-1143, BRILL, 201010.1163/000579510X507001]Search in Google Scholar
[[8] Du, Y. and Belcher, C. and Zhou, Z. and Ives, R.,: Feature correlation evaluation approach for iris feature quality measure, Signal processing, Vol. 90, No. 4, 1176-1187, Elsevier, 201010.1016/j.sigpro.2009.10.001]Search in Google Scholar
[[9] Nill, N. B, IQF (Image Quality of Fingerprint) Software Application, The MITRE Corporation, 2007]Search in Google Scholar
[[10] Crete, F., Dolmiere,T., Ladret, P. and Nicolas, M.: The blur effect: perception and estimation with a new no-reference perceptual blur metric., Human Vision and Electronic Image in XII, 6492:64920I, 2007.]Search in Google Scholar
[[11] Li, Y.H., Savvides, M.: An automatic iris occlusion estimation method based on high-dimensional density estimation., Pattern Analysis Machine Intelligence, IEEE Transactions on, pp 784-9-6,35(4), 2013.10.1109/TPAMI.2012.16922868651]Search in Google Scholar
[[12] Yalamanchili, R. K.: Occlussion Metrics,West virginia University, 2011]Search in Google Scholar
[[13] Bieroza, M. and Baker, A. and Bridgeman, J.,: Classification and calibration of organic matter fluorescence data with multiway analysis methods and artificial neural networks: an operational tool for improved drinking water treatment, Environmetrics, Vol. 22, No.3, 256-270,Wiley Online Library, 201110.1002/env.1045]Search in Google Scholar
[[14] Jeong, D. H. and Ziemkiewicz, C. and Ribarsky, W. and Chang, R. and Center, C. V.,:Understanding Principal Component Analysis Using a Visual Analytics Tool, Charlotte Visualization Center, UNC Charlotte, 2009]Search in Google Scholar
[[15] Suhr, D. D.:Principal component analysis vs. exploratory factor analysis, SUGI 30 Proceedings, 203-230, 2005]Search in Google Scholar
[[16] Proenc¸a, H. and Alexandre, L.A., UBIRIS: A noisy iris image database, International Conference on Image Analysis and Processing, 200510.1007/11553595_119]Search in Google Scholar
[[17] Chinese Academy of Sciences Institute of Automation., CASIA Iris Database,Online: http://biometrics.idealtest.org/dbDetailForUser.do?id=4,2012]Search in Google Scholar
[[18] Fairchild M, D:Color Appearance Models, Slides from a tutorial at the IST/SID 12th Color Imaging Conference, 2004]Search in Google Scholar