Title :
STAG: Semantic Image Annotation Using Relationships between Tags
Author :
Dong-Hyuk Im ; Geun-Duk Park
Author_Institution :
Dept. of Comput. Eng., Hoseo Univ., Asan, South Korea
Abstract :
The state-of-art image tagging system has a limitation in that it allows users to annotate image tags in noun form that cannot fully express the semantics of image. In this paper, we propose a STAG, semi-automatic annotation system for image using semantic relationships between social tags. By connecting the image tags using predicate word, we can capture the contexts in which image tags are used. Compared with ontology-based annotation system, this reduces a large amount of manual jobs and enhances the expression of image content. In addition, we are able to use SPARQL-like query for image retrieval.
Keywords :
image enhancement; image retrieval; word processing; SPARQL-like query; STAG; context capturing; image content expression enhancement; image retrieval; image tagging system; manual job reduction; predicate word; semantic image tag annotation; semantic relationships; semiautomatic annotation system; social tags; Context; Image retrieval; Joining processes; Manuals; Ontologies; Semantics; Tagging;
Conference_Titel :
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location :
Suwon
Print_ISBN :
978-1-4799-0602-4
DOI :
10.1109/ICISA.2013.6579483
