Human Identification Using Multi-region PCA for Iris Recognition

LASZLO, LEFKOVITS and SEPTIMIU, CRISAN and SIMINA, EMERICH and SZIDONIA, LEFKOVITS (2017) Human Identification Using Multi-region PCA for Iris Recognition. In: Fifth International Conference on Advances in Computing, Communication and Information Technology - CCIT 2017, 02-03 September, 2017, Zurich, Switzerland.

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Biometric identification is a constantly growing fie l d. Many physiological characteristics may be used for r eliable identification. T he most secure among them uses the iris pattern , because it is unique and stable from eye to eye and from person to person. The approach presented in this article guides through every step of iris - based human identification system from eye localization to iris extraction and identification using PCA features. The novelty of this paper consists of the application of PCA on multi - region iris images. The PCA identification based on multiple regions of interest (ROI) allows higher ident ification accuracy while extract ing muc h fewer features .

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: iris recognition; eigeniris; PCA; performance evaluation; UPOL database
Depositing User: Mr. John Steve
Date Deposited: 11 Mar 2019 08:31
Last Modified: 11 Mar 2019 08:31

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