An imagination-based query creation method for image retrieval

Diep Thi Ngoc Nguyen, Yasushi Kiyoki

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Our imagination-based query creation method is a new approach to image-recall functions reflecting color-based imaginations in human brains. This method dynamically represents user's imaginations and creates queries for image retrieval. The important aim of this method is to express user's abstract intentions in a computable objects and to recall those imaginations from image databases with color-analytical image retrieval. The main features of this method are: (1) a hierarchical model for color indexing to express image contexts, (2) color zooming for context-dependent color histogram generation by utilizing color names as contextual words, (3) integrating several histograms by using five histogram-combining operations and dynamic semantic weighting, and (4) threshold controlling for semantic correlation. This method exploits color information to retrieve intended images expressing a user's imagination. This paper also represents a 'Database for Imagination Expression' (DBIE), which stores, shares and reuses created queries. Additionally, several qualitative experiments are also represented to examine the effectiveness and the feasibility of our method.

Original languageEnglish
Title of host publicationInformation Modelling and Knowledge Bases XXIV
PublisherIOS Press
Pages201-220
Number of pages20
ISBN (Print)9781614991762
DOIs
Publication statusPublished - 2013

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume251
ISSN (Print)0922-6389

Keywords

  • Context recognition and management
  • Database creation
  • Dynamic query creation
  • Image retrieval
  • Imagination representation

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Nguyen, D. T. N., & Kiyoki, Y. (2013). An imagination-based query creation method for image retrieval. In Information Modelling and Knowledge Bases XXIV (pp. 201-220). (Frontiers in Artificial Intelligence and Applications; Vol. 251). IOS Press. https://doi.org/10.3233/978-1-61499-177-9-201