Journal of Computer Science and Technology

, Volume 20, Issue 6, pp 855–860

Visual Ontology Construction for Digitized Art Image Retrieval

  • Shu-Qiang Jiang
  • Jun Du
  • Qing-Ming Huang
  • Tie-Jun Huang
  • Wen Gao
Article

DOI: 10.1007/s11390-005-0855-x

Cite this article as:
Jiang, SQ., Du, J., Huang, QM. et al. J Comput Sci Technol (2005) 20: 855. doi:10.1007/s11390-005-0855-x

Abstract

Current investigations on visual information retrieval are generally content-based methods. The significant difference between similarity in low-level features and similarity in high-level semantic meanings is still a major challenge in the area of image retrieval. In this work, a scheme for constructing visual ontology to retrieve art images is proposed. The proposed ontology describes images in various aspects, including type & style, objects and global perceptual effects. Concepts in the ontology could be automatically derived. Various art image classification methods are employed based on low-level image features. Non-objective semantics are introduced, and how to express these semantics is given. The proposed ontology scheme could make users more naturally find visual information and thus narrows the “semantic gap”. Experimental implementation demonstrates its good potential for retrieving art images in a human-centered manner.

Keywords

ontology designimage/video retrievalimage database

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Shu-Qiang Jiang
    • 1
    • 2
  • Jun Du
    • 2
  • Qing-Ming Huang
    • 2
  • Tie-Jun Huang
    • 2
  • Wen Gao
    • 1
    • 2
  1. 1.Digital Media Lab, Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R. China
  2. 2.Research Center of Digital MediaGraduate School of the Chinese Academy of SciencesBeijingP.R. China