dc.creatorGarza Castañon, Luis E.
dc.creatorMontes de Oca, Saúl
dc.creatorMorales Menéndez, Rubén
dc.date2006-08
dc.date2006-08
dc.date2012-11-15T17:10:04Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/24249
dc.identifierisbn:0-387-34655-4
dc.descriptionWe present a new approach for iris recognition based on stochastic autoregressive models with exogenous input (ARX). Iris recognition is a method to identify persons, based on the analysis of the eye iris. A typical iris recognition system is composed of four phases: image acquisition and preprocessing, iris localization and extraction, iris features characterization, and comparison and matching. The main contribution in this work is given in the step of characterization of iris features by using ARX models. In our work every iris in database is represented by an ARX model learned from data. In the comparison and matching step, data taken from iris sample are substituted into every ARX model and residuals are generated. A decision of accept or reject is taken based on residuals and on a threshold calculated experimentally. We conduct experiments with two different databases. Under certain conditions, we found a rate of successful identifications in the order of 99.7 % for one database and 100 % for the other.
dc.descriptionApplications in Artificial Intelligence - Applications
dc.descriptionRed de Universidades con Carreras en Informática (RedUNCI)
dc.formatapplication/pdf
dc.languageen
dc.relation19 th IFIP World Computer Congress - WCC 2006
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.subjectCiencias Informáticas
dc.titleAn application of ARX stochastic models to iris recognition
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


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