A New Model for Iris Recognition by Using Artificial Neural Networks
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-10-8672-4_14
Reference15 articles.
1. Fenker SP, Bowyer KW (2011) Experimental evidence of a template aging effect in iris biometrics. In: IEEE computer society workshop on applications of computer vision, pp 232–239
2. Sazonova N, Hua F, Liu X, Remus J, Ross A, et al. (2012) A study on quality-adjusted impact of time lapse on iris recognition. In: Sensing technologies for global health, military medicine, disaster response, and environmental monitoring II; and biometric technology for human identification IX, vol 8371, pp 83711–83719
3. Djekoune O, Messaoudi K, Amara K (2017) Incremental circle Hough transform: an improved method for circle detection. Optik Int J Light Electr Opt 133:17–31
4. Kumar AA, Gupta A (2015) Iris localization based on integro-differential operator for unconstrained infrared iris images. In: 2015 international conference on signal processing, computing and control (ISPCC), Waknaghat, pp 277–281
5. Umer S, Dhara BC, Chanda B (2015) Iris recognition using multiscale morphologic features. Pattern Recogn Lett 65:67–74
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