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Classification and Image Annotation for Bridging the Semantic Gap

Classification and Image Annotation for Bridging the Semantic Gap
Classification and Image Annotation for Bridging the Semantic Gap
The use of digital images is rapidly increasing in digital archives, community databases, as well as on the Web. This creates new challenges for image management and retrieval and promotes the importance of automatic image classification and annotation research. In general current content-based image retrieval methods are still struggling to deal with the semantic gap between low-level visual features and the high-level abstractions perceived by humans. Manual annotation is typically a difficult and tedious task involving a process of describing the content and context of an image to provide direct access to the semantics. Automatic classification can allocate images or image regions to specific object classes and automatic annotation also aims to add descriptive labels to images. This paper will explore classification and image annotation in bridging the semantic gap and present some related projects which illustrate the advantages of these techniques for image retrieval in the medical and cultural heritage domains.
Image classifications, Image annotation
Muda, Zurina
8db47fa1-ffef-41a1-957f-b0eb0b26111e
Muda, Zurina
8db47fa1-ffef-41a1-957f-b0eb0b26111e

Muda, Zurina (2007) Classification and Image Annotation for Bridging the Semantic Gap. Summer School on Multimedia Semantics 2007, University of Glasgow, Glasgow. 15 - 21 Jul 2007.

Record type: Conference or Workshop Item (Poster)

Abstract

The use of digital images is rapidly increasing in digital archives, community databases, as well as on the Web. This creates new challenges for image management and retrieval and promotes the importance of automatic image classification and annotation research. In general current content-based image retrieval methods are still struggling to deal with the semantic gap between low-level visual features and the high-level abstractions perceived by humans. Manual annotation is typically a difficult and tedious task involving a process of describing the content and context of an image to provide direct access to the semantics. Automatic classification can allocate images or image regions to specific object classes and automatic annotation also aims to add descriptive labels to images. This paper will explore classification and image annotation in bridging the semantic gap and present some related projects which illustrate the advantages of these techniques for image retrieval in the medical and cultural heritage domains.

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More information

Published date: 15 July 2007
Additional Information: Event Dates: 15-21 JULY 2007
Venue - Dates: Summer School on Multimedia Semantics 2007, University of Glasgow, Glasgow, 2007-07-15 - 2007-07-21
Keywords: Image classifications, Image annotation
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 265676
URI: http://eprints.soton.ac.uk/id/eprint/265676
PURE UUID: 505079d2-554c-4470-8137-7fe6f899397b

Catalogue record

Date deposited: 08 May 2008 16:58
Last modified: 14 Mar 2024 08:12

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Contributors

Author: Zurina Muda

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