Optimization of Human Recognition from the Iris Images using the Haar wavelet

Subject Areas : Majlesi Journal of Telecommunication Devices

Nahal  Avazpour ¹ (Master student)
Mehran  Emadi ² (signal processing)

Received: 2018-12-26 Accepted : 2018-12-31 Published : 2019-03-01

Keywords: iris identification, Wavelet,

Abstract :

Today, biometric recognition (based on biological signs) is a common and reliable method for recognizing and identity confirmation based on their behavioral and physiological characteristics. Physiological characteristics are consistent with the physical characteristics of individuals such as fingerprints, iris pattern, facial features, and the like. This type of property often does not change without external exertion. Behavioral characteristics such as signature, spoken pattern and iris are also a scale for identification and identity confirmation. In this study, using the wavelet method, the efficiency of human identification was increased by 75%.

References:

[1] J. Daugman, How iris recognition works inImage Processing. 2002. Proceedings. 2002International Conference on, 2002, pp. I-33-I-36vol.1.

[2] T. C. M. DellaVecchia, T. Camus, M.Salganicoff, M. Negin, Methodology andApparatus for Using the Human Iris as a RobustBiometric, SPIE Oph. Tech. 1998.

[3]A. Haro, M. Flickner, and I. Essa, Detecting andtracking eyes by using theirphysiologicalproperties, dynamics, and appearance, in ComputerVision and PatternRecognition, 2000. Proceedings.IEEE Conference on, 2000, pp. 163-168 vol.1.

[4]L. M. C. Tisse, L. Torres, M. Robert. Personidentification technique using human iris recognition, International Conference on VisionInterface, Canada, 2002.

[5]R. P. Wildes, J. C. Asmuth, G. L. Green, S. C.Hsu, R. J. Kolczynski, J. R. Matey, et al. A system for automated iris recognition, in Applications of Computer Vision, 1994.Proceedings of the SecondIEEE Workshop on, 1994, pp. 121-128.

[6]W. K. Kong and D. Zhang, Accurate irissegmentation based on novel reflection and eyelashdetection model, in Intelligent Multimedia, Video and Speech Processing, 2001. Proceedings of 2001 International Symposium on, 2001, pp. 263-266. [7]V. G. Garagad, N. C. Iyer A Novel Technique of Iris Identification for Biometric Systems 2014, IEEE,978-1-4799-3080-7

[8]R. Hidayat Abiyev and K. Altunkaya Neural Network Based Biometric Personal Identification with Fast Iris Segmentation International Journal of Control, Auto motion, and Systems, 2009, springer 10.1007/s12555-009-0103-1

[9] S. Umera, B. Chandra Dharab, b. Chanda Iris Recognition using Multi scale Morphologic Features 2015, ELSEVIER, S0167-8655(15)00211-1

[10] Benesty Study of the Wiener Filter for Noise Reduction, Part of the Signals and Communication Technology book series (SCT)