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<record>
  <title>Model-Driven Development of Content-Based Image Retrieval Systems</title>
  <journal>Journal of Digital Information Management</journal>
  <author>Temenushka Ignatova, Andreas Heuer</author>
  <volume>6</volume>
  <issue>1</issue>
  <year>2008</year>
  <doi></doi>
  <url>http://www.dirf.org/jdim/v6n1a9.asp</url>
  <abstract>Generic systems for content-based image retrieval (CBIR), such as QBIC [7] cannot be used to solve domain-specific image retrieval problems, as for example, the identification of manuscript writers based on the visual characteristics of their handwriting. Domain-specific CBIR systems currently have to be implemented bottom up, i.e. almost from scratch, each time a new domain-specific solution is sought. Inspired by the recognition, that CBIR systems, although developed for different domain-problems, comprise similar building blocks and architecture, the idea of adopting model-driven development techniques for generating CBIR systems was elaborated. To support the design of domainspecific CBIR-Systems on a conceptual level by reusing data structure and functional interfaces a framework model is developed, which can be used to derive concrete domainspecific CBIR models. A transformation approach for the generation of a platform-specific implementation on top of an object-relational database from the concrete conceptual model is proposed. Finally, how these techniques can be applied for the design of a CBIR system for the identification of music manuscript writers based on the visual characteristics of their handwriting is demonstrated.</abstract>
</record>
