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Managing Uncertainties in Image Databases

Managing Uncertainties in Image Databases
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Author(s): Antonio Picariello (University of Napoli, Italy)and Maria Luisa Sapino (University of Torino, Italy)
Copyright: 2009
Pages: 17
Source title: Database Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Erickson (University of Nebraska, Omaha, USA)
DOI: 10.4018/978-1-60566-058-5.ch139

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Abstract

In this chapter, we focus on those functionalities of multimedia databases that are not present in traditional databases but are needed when dealing with multimedia information. Multimedia data are inherently subjective; for example, the association of a meaning and the corresponding content description of an image as well as the evaluation of the differences between two images or two pieces of music usually depend on the user who is involved in the evaluation process. For retrieval, such subjective information needs to be combined with objective information, such as image color histograms or sound frequencies, that is obtained through (generally imprecise) data analysis processes. Therefore, the inherently fuzzy nature of multimedia data, both at subjective and objective levels, may lead to multiple, possibly inconsistent, interpretations of data. Here, we present the FNF2 data model, a Non-First Normal Form extension of the relational model, which takes into account subjectivity and fuzziness while being intuitive and enabling user-friendly information access and manipulation mechanisms.

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