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Proceedings Paper

Ontology driven image search engine
Author(s): Yun Bei; Julia Dmitrieva; Mounia Belmamoune; Fons J. Verbeek
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Paper Abstract

Image collections are most often domain specific. We have developed a system for image retrieval of multimodal microscopy images. That is, the same object of study visualized with a range of microscope techniques and with a range of different resolutions. In microscopy, image content is depending on the preparation method of the object under study as well as the microscope technique. Both are taken into account in the submission phase as metadata whilst at the same time (domain specific) ontologies are employed as controlled vocabularies to annotate the image. From that point onward, image data are interrelated through the relationships derived from annotated concepts in the ontology. By using concepts and relationships of an ontology, complex queries can be built with true semantic content. Image metadata can be used as powerful criteria to query image data which are directly or indirectly related to original data. The results of image retrieval can be represented using a structural graph by exploiting relationships from ontology rather than a listed table. Applying this to retrieve images from the same subject at different levels of resolution opens a new field for the analysis of image content.

Paper Details

Date Published: 29 January 2007
PDF: 10 pages
Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060G (29 January 2007); doi: 10.1117/12.714071
Show Author Affiliations
Yun Bei, Leiden Univ. (Netherlands)
Julia Dmitrieva, Leiden Univ. (Netherlands)
Mounia Belmamoune, Leiden Univ. (Netherlands)
Fons J. Verbeek, Leiden Univ. (Netherlands)

Published in SPIE Proceedings Vol. 6506:
Multimedia Content Access: Algorithms and Systems
Alan Hanjalic; Raimondo Schettini; Nicu Sebe, Editor(s)

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