Title: Metadata-based automatic image tagging

Authors: Randi Karlsen; Martin Hætta Evertsen; Najeeb Elahi

Addresses: Department of Computer Science, UiT the Arctic University of Norway, 9037 Tromsø, Norway ' Department of Computer Science, UiT the Arctic University of Norway, 9037 Tromsø, Norway ' Department of Computer Science, UiT the Arctic University of Norway, 9037 Tromsø, Norway

Abstract: Today, keyword-based search is the most common technique for searching images, and requires the availability of tags and annotations that reflect image content. While there are many techniques for automatic annotation based on image content analysis, less work has utilised image metadata as a basis for image tagging. We investigate the ability to automatically tag images based solely on image metadata, and present a novel approach to image tagging using a combination of the metadata geo-location, date/time and category keyword. We aim to collect relevant tags for a target image by selecting tags from related images on a community image collection, such as Flickr. Contributions of our approach are the use of dynamic techniques that adapt tag selection to the availability of relevant images and tags in the community collection. Through testing we demonstrate the usefulness of the techniques and the use of metadata information in the image tagging process.

Keywords: automatic image tagging; image metadata; metadata-based tagging; image retrieval; textual search; tag selection; dynamic techniques; content relevant tags.

DOI: 10.1504/IJMSO.2013.058412

International Journal of Metadata, Semantics and Ontologies, 2013 Vol.8 No.4, pp.298 - 308

Received: 05 Nov 2012
Accepted: 03 Oct 2013

Published online: 14 Oct 2014 *

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