Model-Driven Development of Content-Based Image Retrieval Systems
Temenushka Ignatova, Andreas Heuer
Journal of Digital Information Management, Vol. 6, No. 1, 2008.
DOI: 
Link: http://www.dirf.org/jdim/v6n1a9.asp
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.