Efficient Iris Recognition Management in Object-Related Databases

Biometric applications have grown significantly in recent years, particularly iris-based systems. In the present work, an extension of an Object Relational Database Management System for the integral management of a biometric system based on the human iris was presented. Although at present, there a...

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Detalles Bibliográficos
Autores principales: Alvez, Carlos E., Miranda, Ernesto, Etchart, Graciela, Ruíz, Silvia
Formato: Articulo
Lenguaje:Inglés
Publicado: 2018
Materias:
Ciencias Informáticas
Base de Datos
índice
IrisCode
index
database
object relational
extension
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/70113
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-70113
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
Base de Datos
índice
IrisCode
index
database
object relational
extension
spellingShingle Ciencias Informáticas
Base de Datos
índice
IrisCode
index
database
object relational
extension
Alvez, Carlos E.
Miranda, Ernesto
Etchart, Graciela
Ruíz, Silvia
Efficient Iris Recognition Management in Object-Related Databases
topic_facet Ciencias Informáticas
Base de Datos
índice
IrisCode
index
database
object relational
extension
description Biometric applications have grown significantly in recent years, particularly iris-based systems. In the present work, an extension of an Object Relational Database Management System for the integral management of a biometric system based on the human iris was presented. Although at present, there are many database extensions for different domains, in no case for biometric applications. The proposed extension includes both the extension of the type system and the definition of domain indexes for performance improvement. The aim of this work is to provide a tool that facilitates the development of biometric applications based on the iris feature. Its development is based on a reference architecture that includes both the management of images of the iris trait, its associated metadata and the necessary methods for both manipulation and queries. An implementation of the extension is performed for PostgreSQL DBMS, and SP-GiST framework is used in the implementation of a domain index. Experiments were carried out to evaluate the performance of the proposed index, which shows improvements in query execution times.
format Articulo
Articulo
author Alvez, Carlos E.
Miranda, Ernesto
Etchart, Graciela
Ruíz, Silvia
author_facet Alvez, Carlos E.
Miranda, Ernesto
Etchart, Graciela
Ruíz, Silvia
author_sort Alvez, Carlos E.
title Efficient Iris Recognition Management in Object-Related Databases
title_short Efficient Iris Recognition Management in Object-Related Databases
title_full Efficient Iris Recognition Management in Object-Related Databases
title_fullStr Efficient Iris Recognition Management in Object-Related Databases
title_full_unstemmed Efficient Iris Recognition Management in Object-Related Databases
title_sort efficient iris recognition management in object-related databases
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/70113
work_keys_str_mv AT alvezcarlose efficientirisrecognitionmanagementinobjectrelateddatabases
AT mirandaernesto efficientirisrecognitionmanagementinobjectrelateddatabases
AT etchartgraciela efficientirisrecognitionmanagementinobjectrelateddatabases
AT ruizsilvia efficientirisrecognitionmanagementinobjectrelateddatabases
AT alvezcarlose gestioneficientedereconocimientodelirisenbasesdedatosobjetosrelacionales
AT mirandaernesto gestioneficientedereconocimientodelirisenbasesdedatosobjetosrelacionales
AT etchartgraciela gestioneficientedereconocimientodelirisenbasesdedatosobjetosrelacionales
AT ruizsilvia gestioneficientedereconocimientodelirisenbasesdedatosobjetosrelacionales
bdutipo_str Repositorios
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