Concept Based Image Retrieval Using the Domain Ontology

The recent study has been progressed the research about more semantic image indexing and retrieval. In our paper, we represent the improved concept-based image retrieval by using domain ontology. We analyze the many studies that applied the theory of ontology to concept-based image retrieval. Then, we try to solve the problems when we apply the huge ontologies in image retrieval system. There are two big problems. First, the huge ontologies that have many concepts, especially in particular domain, cannot express in existing ontologies. Therefore, in this paper we try to design and implement the domain ontology about the car based on the WordNet, which is one kinds of ontologies. The experimental result shows that the semantic distances between words are quite close when we test domain ontology than the existing WordNet.

[1]  Shih-Fu Chang,et al.  A conceptual framework and empirical research for classifying visual descriptors , 2001 .

[2]  Jeff Heflin,et al.  SHOE: A Knowledge Representation Language for Internet Applications , 1999 .

[3]  W. Grosky,et al.  An Image Data Model , 2000, VISUAL.

[4]  Vittorio Castelli,et al.  Image Databases: Search and Retrieval of Digital Imagery , 2002 .

[5]  Hans Chalupsky.  Tools for Assembling and Managing Scalable Knowledge Bases , 2003 .

[6]  F. Golshani,et al.  The role of color in content-based image retrieval , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[7]  Shih-Fu Chang,et al.  IMKA: a multimedia organization system combining perceptual and semantic knowledge , 2001, MULTIMEDIA '01.

[8]  Shih-Fu Chang,et al.  Conceptual framework for indexing visual information at multiple levels , 1999, Electronic Imaging.

[9]  David A. Forsyth,et al.  Learning the semantics of words and pictures , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[10]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[11]  Sethuraman Panchanathan,et al.  Concept-Based Visual Information Management with Large Lexical Corpus , 2001, DEXA.

[12]  Sethuraman Panchanathan,et al.  Conceptualization and ontology: tools for efficient storage and retrieval of semantic visual information , 2000, SPIE Optics East.

[13]  David A. Forsyth,et al.  Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary , 2002, ECCV.