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Foundation of the DISIMA Image Query Languages

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Abstract

Because digital images are not meaningful by themselves, images are often coupled with some descriptive or qualitative data in an image database. These data, divided into syntactic (color, shape, and texture) and semantic (meaningful real word object or concept) features, necessitate novel querying techniques. Most image systems and prototypes have focussed on similarity searches based upon the syntactic features. In the DISIMA system, we proposed an object-oriented image data model that introduces two main types: image (that represents an image and its descriptive properties) and salient object (that represents the semantics of an image). We further defined operations on the images and the salient objects as new joins. This approach is necessary in order to envision a declarative query language for images. This paper summarizes the querying facilities implemented for the DISIMA system and gives their theoretical foundation: the data model and the complementary algebraic operations, the textual query language (MOQL) and its visual counterpart (VisualMOQL) based on an image calculus. Both languages are declarative and allow the combination of semantic and similarity queries.

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Authors and Affiliations

  1. Department of Computer Science, New Jersey Institute of Technology, USA

    Vincent Oria

  2. School of Computer Science, University of Waterloo, Canada

    M. Tamer Özsu

  3. Department of Electrical & Computer Engineering, University of Alberta, Canada

    Paul J. Iglinski

Authors
  1. Vincent Oria
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  2. M. Tamer Özsu
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  3. Paul J. Iglinski
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Oria, V., Özsu, M.T. & Iglinski, P.J. Foundation of the DISIMA Image Query Languages. Multimedia Tools and Applications 23, 185–201 (2004). https://doi.org/10.1023/B:MTAP.0000031756.10332.9d

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  • DOI: https://doi.org/10.1023/B:MTAP.0000031756.10332.9d

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