An application of ARX stochastic models to iris recognition
We 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 preproces...
Guardado en:
| Autores principales: | , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2006
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/24249 |
| Aporte de: |
| id |
I19-R120-10915-24249 |
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| record_format |
dspace |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Ciencias Informáticas Biometría iris recognition systems |
| spellingShingle |
Ciencias Informáticas Biometría iris recognition systems Garza Castañon, Luis E. Montes de Oca, Saúl Morales Menéndez, Rubén An application of ARX stochastic models to iris recognition |
| topic_facet |
Ciencias Informáticas Biometría iris recognition systems |
| description |
We 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. |
| format |
Objeto de conferencia Objeto de conferencia |
| author |
Garza Castañon, Luis E. Montes de Oca, Saúl Morales Menéndez, Rubén |
| author_facet |
Garza Castañon, Luis E. Montes de Oca, Saúl Morales Menéndez, Rubén |
| author_sort |
Garza Castañon, Luis E. |
| title |
An application of ARX stochastic models to iris recognition |
| title_short |
An application of ARX stochastic models to iris recognition |
| title_full |
An application of ARX stochastic models to iris recognition |
| title_fullStr |
An application of ARX stochastic models to iris recognition |
| title_full_unstemmed |
An application of ARX stochastic models to iris recognition |
| title_sort |
application of arx stochastic models to iris recognition |
| publishDate |
2006 |
| url |
http://sedici.unlp.edu.ar/handle/10915/24249 |
| work_keys_str_mv |
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Repositorios |
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