DOGI: an annotation system for images of dog breeds

Authors:
Antonios Dimas;Pyrros Koletsis;Euripides G. M. Petrakis
Affiliations:
Department of Electronic and Computer Engineering, Technical University of Crete (TUC), Chania, Crete, Greece;Department of Electronic and Computer Engineering, Technical University of Crete (TUC), Chania, Crete, Greece;Department of Electronic and Computer Engineering, Technical University of Crete (TUC), Chania, Crete, Greece
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Year:
2012

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Abstract

DOGI (D og O ntoloG y I mage annotator) is a complete and fully automated semantic annotation system for images of dog breeds. Annotation relies on feature extraction and on associating low-level features with image concepts in an ontology. Because general purpose ontologies for all image types are not yet available, we choose the problem of annotating images of dog breeds as a case study and for the evaluation of our methodology. Nevertheless, DOGI can be adapted to more image types provided that an ontology for a new image domain becomes available. Therefore, DOGI offers an ideal test-bed for experimentation and sets the grounds for the annotation and evaluation of virtually any image type. Evaluation results are realized using images collected from the Web. Almost 95% of the test images is correctly annotated (i.e., DOGI identified their class correctly). DOGIis accessible on the Internet.