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| Autor principal: | |
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| Formato: | Artículo científico |
| Lenguaje: | en |
| Publicado: |
Universidad Nacional de La Plata
2018
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| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=638067787001 https://www.redalyc.org/journal/6380/638067787001/ https://www.redalyc.org/journal/6380/638067787001/html/ https://www.redalyc.org/journal/6380/638067787001/638067787001.epub https://www.redalyc.org/journal/6380/638067787001/movil https://doi.org/10.24215/16666038.18.e12 |
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- Efficient Iris Recognition Management in Object-Related Databases Carlos Alvez Ernesto Miranda Graciela Etchart Silvia Ruiz Computación index IrisCode database extension object relational 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. 2018 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067787001 https://www.redalyc.org/journal/6380/638067787001/ https://www.redalyc.org/journal/6380/638067787001/html/ https://www.redalyc.org/journal/6380/638067787001/638067787001.epub https://www.redalyc.org/journal/6380/638067787001/movil https://doi.org/10.24215/16666038.18.e12 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.2 Vol.18