Multiple regions and their spatial relationship-based image retrieval

Byoungchul Ko, Hyeran Byun

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

6 Citations (Scopus)

Abstract

In this paper, we present a new multiple regions and their spatial relationship-based image retrieval method. In this method, a semantic object is integrated as a set of related regions based on their spatial relationships and visual features. In contrast to other ROI (Regionof- Interest) or multiple region-based algorithms, we use the Hausdorff Distance (HD) to estimate spatial relationships between regions. By our proposed HD, we can simplify matching process between complex spatial relationships and admit spatial variations of regions, such as translation, rotation, insertion, and deletion. Furthermore, to solve the weight adjust problem automatically and to reflect user’s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.

Original languageEnglish
Title of host publicationImage and Video Retrieval - International Conference, CIVR 2002, Proceedings
EditorsMichael S. Lew, Nicu Sebe, John P. Eakins
PublisherSpringer Verlag
Pages81-90
Number of pages10
ISBN (Electronic)9783540438991
Publication statusPublished - 2002 Jan 1
EventInternational Conference on Image and Video Retrieval, CIVR 2002 - London, United Kingdom
Duration: 2002 Jul 182002 Jul 19

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

Other

OtherInternational Conference on Image and Video Retrieval, CIVR 2002
CountryUnited Kingdom
CityLondon
Period02/7/1802/7/19

Fingerprint

Image retrieval
Image Retrieval
Semantics
Feedback
Hausdorff Distance
Relevance Feedback
Similarity Measure
Deletion
Insertion
Simplify
Relationships
Estimate

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ko, B., & Byun, H. (2002). Multiple regions and their spatial relationship-based image retrieval. In M. S. Lew, N. Sebe, & J. P. Eakins (Eds.), Image and Video Retrieval - International Conference, CIVR 2002, Proceedings (pp. 81-90). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2383). Springer Verlag.
Ko, Byoungchul ; Byun, Hyeran. / Multiple regions and their spatial relationship-based image retrieval. Image and Video Retrieval - International Conference, CIVR 2002, Proceedings. editor / Michael S. Lew ; Nicu Sebe ; John P. Eakins. Springer Verlag, 2002. pp. 81-90 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Ko, B & Byun, H 2002, Multiple regions and their spatial relationship-based image retrieval. in MS Lew, N Sebe & JP Eakins (eds), Image and Video Retrieval - International Conference, CIVR 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2383, Springer Verlag, pp. 81-90, International Conference on Image and Video Retrieval, CIVR 2002, London, United Kingdom, 02/7/18.

Multiple regions and their spatial relationship-based image retrieval. / Ko, Byoungchul; Byun, Hyeran.

Image and Video Retrieval - International Conference, CIVR 2002, Proceedings. ed. / Michael S. Lew; Nicu Sebe; John P. Eakins. Springer Verlag, 2002. p. 81-90 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2383).

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

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AB - In this paper, we present a new multiple regions and their spatial relationship-based image retrieval method. In this method, a semantic object is integrated as a set of related regions based on their spatial relationships and visual features. In contrast to other ROI (Regionof- Interest) or multiple region-based algorithms, we use the Hausdorff Distance (HD) to estimate spatial relationships between regions. By our proposed HD, we can simplify matching process between complex spatial relationships and admit spatial variations of regions, such as translation, rotation, insertion, and deletion. Furthermore, to solve the weight adjust problem automatically and to reflect user’s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.

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M3 - Conference contribution

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Ko B, Byun H. Multiple regions and their spatial relationship-based image retrieval. In Lew MS, Sebe N, Eakins JP, editors, Image and Video Retrieval - International Conference, CIVR 2002, Proceedings. Springer Verlag. 2002. p. 81-90. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).