Content-based image retrieval using wavelet-based salient points

Q. Tian, N. Sebe, M. S. Lew, E. Loupias, T. S. Huang

Research output: Contribution to journalArticlepeer-review


Content-based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Most of the attention from the research has been focused on indexing techniques based on global feature distributions. However, these global distributions have limited discriminating power because they are unable to capture local image information. Applying global Gabor texture features greatly improve the retrieval accuracy. But they are computationally complex. In this paper, we present a wavelet-based salient point extraction algorithm. We show that extracting the color and texture information in the locations given by these points provides significantly improved results in terms of retrieval accuracy, computational complexity and storage space of feature vectors as compared to the global feature approaches.

Original languageEnglish (US)
Pages (from-to)425-436
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2001
Externally publishedYes


  • CBIR
  • Gabor filter
  • Haar wavelet
  • Wavelet-based salient points

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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