Abstract
In this article, an architecture for image retrieval in an Object-Relational Database Management System is proposed. It combines the use of low-level descriptors and semantic metadata for similarity search. The architecture has three levels: content-based, semantic data and an interface integrating them. Several database User Defined Types (UDT) and operations are defined for that purpose. A case study about vehicles is implemented and results obtained show an important improvement in image similarity search.
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Alvez, C.E., Vecchietti, A.R. (2010). Combining Semantic and Content Based Image Retrieval in ORDBMS. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_5
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DOI: https://doi.org/10.1007/978-3-642-15390-7_5
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