Multiple regions and their spatial relationship-based image retrieval

Byoungchul Ko; Hyeran Byun

doi:10.1007/3-540-45479-9_9

Multiple regions and their spatial relationship-based image retrieval

Byoungchul Ko, Hyeran Byun

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Image and Video Retrieval - International Conference, CIVR 2002, Proceedings
Editors	Michael S. Lew, Nicu Sebe, John P. Eakins
Publisher	Springer Verlag
Pages	81-90
Number of pages	10
ISBN (Electronic)	9783540438991
DOIs	https://doi.org/10.1007/3-540-45479-9_9
Publication status	Published - 2002
Event	International Conference on Image and Video Retrieval, CIVR 2002 - London, United Kingdom Duration: 2002 Jul 18 → 2002 Jul 19

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2383
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	International Conference on Image and Video Retrieval, CIVR 2002
Country	United Kingdom
City	London
Period	02/7/18 → 02/7/19

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-45479-9_9

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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. https://doi.org/10.1007/3-540-45479-9_9

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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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{\textquoteright}s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.",

author = "Byoungchul Ko and Hyeran Byun",

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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. https://doi.org/10.1007/3-540-45479-9_9

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 proceeding › Conference contribution

TY - GEN

T1 - Multiple regions and their spatial relationship-based image retrieval

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N2 - 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.

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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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Image and Video Retrieval - International Conference, CIVR 2002, Proceedings

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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)). https://doi.org/10.1007/3-540-45479-9_9

Multiple regions and their spatial relationship-based image retrieval

Abstract

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Bibliographical note

All Science Journal Classification (ASJC) codes

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