Abstract
DOG I (Dog OntoloGy Image 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, DOG I can be adapted to more image types provided that an ontology for a new image domain becomes available. Therefore, DOG I 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., DOG I identified their class correctly). DOG I is accessible on the Internet.
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Dimas, A., Koletsis, P., Petrakis, E.G.M. (2012). DOG I : An Annotation System for Images of Dog Breeds. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31295-3_48
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DOI: https://doi.org/10.1007/978-3-642-31295-3_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31294-6
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