Evaluation of salient point techniques

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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 usingt he criteria: repeatability rate and information content. We also show that extractingc olor 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)
Title of host publicationImage and Video Retrieval - International Conference, CIVR 2002, Proceedings
EditorsMichael S. Lew, Nicu Sebe, John P. Eakins
Number of pages11
ISBN (Electronic)9783540438991
StatePublished - 2002
EventInternational Conference on Image and Video Retrieval, CIVR 2002 - London, United Kingdom
Duration: Jul 18 2002Jul 19 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference on Image and Video Retrieval, CIVR 2002
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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