Automatic semantic annotation of real-world web images

Roger C.F. Wong*, Clement H C Leung

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

73 Citations (Scopus)


As the number of web images is increasing at a rapid rate, searching them semantically presents a significant challenge. Many raw images are constantly uploaded with little meaningful direct annotations of semantic content, limiting their search and discovery. In this paper, we present a semantic annotation technique based on the use of image parametric dimensions and metadata. Using decision trees and rule induction, we develop a rule-based approach to formulate explicit annotations for images fully automatically, so that by the use of our method, semantic query such as "sunset by the sea in autumn in New York" can be answered and indexed purely by machine. Our system is evaluated quantitatively using more than 100,000 web images. Experimental results indicate that this approach is able to deliver highly competent performance, attaining good recall and precision rates of sometimes over 80%. This approach enables a new degree of semantic richness to be automatically associated with images which previously can only be performed manually.

Original languageEnglish
Pages (from-to)1933-1944
Number of pages12
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number11
Publication statusPublished - Nov 2008

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

User-Defined Keywords

  • Decision trees
  • Feature extraction
  • Image annotation
  • Image retrieval
  • Image semantics
  • Metadata
  • Rule induction
  • Scene analysis


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