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Semantics-based image retrieval by region saliency

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

28 Scopus citations

Abstract

We propose a new approach for semantics-based image retrieval. We use color-texture classification to generate the codebook which is used to segment images into regions. The content of a region is characterized by its self-saliency and the lower-level features of the region, including color and texture. The context of regions in an image describes their relationships, which are related to their relative-saliencies. High-level (semantics-based) querying and query-by-example are supported on the basis of the content and context of image regions. The experimental results demonstrate the effectiveness of our approach.

Original languageEnglish
Title of host publicationImage and Video Retrieval - International Conference, CIVR 2002, Proceedings
EditorsMichael S. Lew, Nicu Sebe, John P. Eakins
PublisherSpringer Verlag
Pages29-37
Number of pages9
ISBN (Electronic)9783540438991
DOIs
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)
Volume2383
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Image and Video Retrieval, CIVR 2002
Country/TerritoryUnited Kingdom
CityLondon
Period07/18/0207/19/02

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