JOURNAL OF MULTIMEDIA (JMM)
ISSN : 1796-2048
Volume : 4 Issue : 5 Date : October 2009
Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval
Kraisak Kesorn and Stefan Poslad
Full Text: PDF (666 KB)
The rapid growth in the volume of visual information can make the task of finding and accessing
visual information of interest, overwhelming for users. Semantic analysis of image captions can be
used in conjunction with image retrieval systems (IMR) to retrieve selected images more precisely.
To do this, we first exploit a Natural Language Processing (NLP) framework in order to extract
concepts from image captions. Next, an ontology-based framework is deployed in order to resolve
natural language ambiguities. The novelty of the proposed framework is that the combination of LSI
with the Ontology framework enables the combined framework to tolerate ambiguities and
variations in the Ontology. A key feature is that the system can find indirectly relevant concepts in
image captions and thus leverage these to represent the semantics of images at a higher level.
Experimental results show that the use of LSI based NLP combined with an ontological framework
significantly enhances image retrieval.
image retrieval, latent semantic indexing, natural language processing, knowledge base, semantic