Content-based image retrieval using similarity

Robert J. Curry, Michael M. Marefat, Fan Yang

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

Abstract

with the fast increase in digital image data and its broad applications, an efficient image retrieval system is demanded. This paper proposes a content-based image retrieval system using similarity that capitalizes on the complementary advantages of both current methods, which are Retrieval by Image Example (RIE) and Retrieval by Semantic Content (RSC). A list of exemplar images is generated from a content-based image synthesis system, and then is used as examples in a GNU Image Finding Tool (GIFT) for image matching. Queries on battlefield images will be tested as experiments and the results are discussed for different two image matching algorithms. The analysis on the results show that image retrieval through semantic queries can be accomplished using the approach described in this paper.

Original languageEnglish (US)
Title of host publication2005 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS'05
Subtitle of host publicationModeling, Exploration, and Engineering
Pages629-634
Number of pages6
DOIs
StatePublished - 2005
Event2005 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS'05: Modeling, Exploration, and Engineering - Waltham, MA, United States
Duration: Apr 18 2005Apr 21 2005

Publication series

Name2005 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS'05: Modeling, Exploration, and Engineering
Volume2005

Other

Other2005 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS'05: Modeling, Exploration, and Engineering
Country/TerritoryUnited States
CityWaltham, MA
Period4/18/054/21/05

ASJC Scopus subject areas

  • General Engineering

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