Evaluation of salient point techniques

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

Research output: Contribution to journalArticlepeer-review


In image retrieval, global features related to color or texture are commonly used to describe the image content. The problem with this approach is that these global features cannot capture all parts of the image having different characteristics. Therefore, local computation of image information is necessary. By using salient points to represent local information, more discriminative features can be computed. In this paper, we compare a wavelet-based salient point extraction algorithm with two corner detectors using the criteria: repeatability rate and information content. We also show that extracting color and texture information in the locations given by our salient points provides significantly improved results in terms of retrieval accuracy, computational complexity, and storage space of feature vectors as compared to global feature approaches.

Original languageEnglish (US)
Pages (from-to)1087-1095
Number of pages9
JournalImage and Vision Computing
Issue number13-14
StatePublished - Dec 1 2003


  • Information content
  • Repeatability rate
  • Salient points
  • Wavelet transform

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition


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