Article

An efficient core-area detection algorithm for fast noise-free image query processing

Authors:

Khanh Vu,

Kien A. Hua,

Duc A. TranAuthors Info & Claims

SAC '01: Proceedings of the 2001 ACM symposium on Applied computing

Pages 258 - 263

https://doi.org/10.1145/372202.372337

Published: 01 March 2001 Publication History

Get Access

References

[1]

http://www.cs.ucf.edu/~ khanh/code.]]

Google Scholar

[2]

P. Andleigh and K. Thakrar. Multimedia Systems Design. Prentice Hall, New York, 1996.]]

Digital Library

Google Scholar

[3]

N. Beckman, H. Kriegel, R. Schneider, and B. Seeger. The r*-tree: an effient and robust access method for points and rectangles. In ACM SIGMOD, pages 322-331, May 1990.]]

Digital Library

Google Scholar

[4]

D. Chetverikov. Detecting regular structures for invariant retrieval. In Third International Conference on Visual Information Systems, pages 459-466, 1999.]]

Digital Library

Google Scholar

[5]

C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Petkovic, and R. Barber. Efficient and effective querying by image content. Journal of Intelligent Information Systems, 3(3):231-262, 1994.]]

Digital Library

Google Scholar

[6]

Y. Gong, H.Chua, and X. Guo. Image indexing and retrieval based on color histogram. In Proc. of the 2nd Int. Conf. on Multimedia Modeling, pages 115-126, November 1995.]]

Google Scholar

[7]

M. Hiyahara and Y. Yoshida. Mathematical transform of (r, g, b) color data to munsell (h, v, c) color data. In SPIE Visual Communications and Image Processing, pages 650-657, 1988.]]

Google Scholar

[8]

K. A. Hua, K. Vu, and J. Oh. Sammatch: A exible and efficient sampling-based image retrieval technique for large image databases. In Proc. of the 1999 ACM International Multimedia Conference, pages 225-234, Oct 1999.]]

Digital Library

Google Scholar

[9]

J. Huang, S. R. Kumar, M. Mitra, W. Zhu, and R. Zabih. Image indexing using color correlograms. In Proc. Computer Vision and Pattern Recognition, pages 762-768, 1997.]]

Digital Library

Google Scholar

[10]

W. Ma and B. Manjunath. Netra: A toolbox for navigating large image databases. Multimedia System, 7:184-198, May 1999.]]

Digital Library

Google Scholar

[11]

J. Malki, N. Boujemaa, C. Nastar, and A. Winter. Region queries without segmentation for image retrieval by content. In Third International Conference on Visual Information and Information Systems, pages 115-122, 1999.]]

Digital Library

Google Scholar

[12]

A. Natsev, R. Rastogi, and K. Shim. Walrus: A similarity retrieval algorithm for image databases. In Proc. of the 1999 ACM SIGMOD Int. Conf. on Management of Data, pages 395-406, 1999.]]

Digital Library

Google Scholar

[13]

N. Nes and M. d'Ornellas. Color image texture idexing. In Third International Conference on Visual Information Systems, pages 467-474, 1999.]]

Digital Library

Google Scholar

[14]

W. Niblack, R. Barber, W. Equitz, M. Flicker, E. Glasman, D. Petkovic, P. Yanker, and C. Faloutsos. The qbic project: Query images by content using color, texture and shape. In SPIE V1908, 1993.]]

Google Scholar

[15]

S. Ravela, R. Manmatha, and E. Riseman. Image retrieval using scale-space matching. In Proc. of the Fourth European Conf. On Computer Vision, pages 273-282, 1996.]]

Digital Library

Google Scholar

[16]

J. R. Smith. Integrated Spatial and Feature Image Systems: Retrieval, Compression and Analysis. PhD thesis, Graduate School of Arts and Science, Columbia University, Feb. 1997.]]

Google Scholar

[17]

M. Swain. Interactive indexing into image database. In SPIE V1908, 1993.]]

Google Scholar

[18]

A. Watt and F. Policarpo. The Computer Image. ACM Press, New York, 1999.]]

Digital Library

Google Scholar

[19]

M. Wood, N. Campbell, and B. Thomas. Iterative reffinement by relevance feedback in content-based digital image retrieval. In The Sixth ACM International Multimedia Conference, pages 13-20, September 1998.]]

Digital Library

Google Scholar

[20]

J. Xu. Morphological decomposition of 2-d binary shapes into conditionally maximal convex polygons. In Pattern Recognition, volume 29, pages 1075-1104, 1996.]]

Digital Library

Google Scholar

[21]

Y. Zhao and R. Haralick. Binary shape recognition based on an automatic morphological shape decomposition. In Proc. of Int. Conf. Acoust., Sign. Proceesing, pages 1691-1694, 1989.]]

Crossref

Google Scholar

Cited By

View all

Tungkasthan APremchaiswadi W(2011)Automatic region of interest detection in natural imagesProceedings of the 15th WSEAS international conference on Computers10.5555/2028299.2028380(437-444)Online publication date: 15-Jul-2011
https://dl.acm.org/doi/10.5555/2028299.2028380
Tungkatsathan APremchaiswadi WPremchaiswadi N(2010)Unsupervised Detection for Minimizing a Region of Interest around Distinct Object in Natural ImagesProceedings of the 2010 International Conference on Digital Image Computing: Techniques and Applications10.1109/DICTA.2010.45(202-207)Online publication date: 1-Dec-2010
https://dl.acm.org/doi/10.1109/DICTA.2010.45
Hiransakolwong N(2005)Automated liver detection in ultrasound imagesProceedings of the 4th international conference on Image and Video Retrieval10.1007/11526346_65(619-628)Online publication date: 20-Jul-2005
https://dl.acm.org/doi/10.1007/11526346_65
Show More Cited By

Index Terms

Recommendations

Towards Interactive Image Query System for Content-Based Image Retrieval
SMAP '09: Proceedings of the 2009 Fourth International Workshop on Semantic Media Adaptation and Personalization

This paper presents an interface of image query system for content-based image retrieval.The proposed interface can split images into the regions and select an target region from the separated regions. We apply content-based image retrieval to the ...
An efficient semantic Related image retrieval method

Retrieving semantic images spread out in the entire feature space.Determining the semantic weight of each query in combined distance calculation.Identifying the importance for each feature.Our method is quite effective, improving the retrieval in one ...
Image retrieval based on bag of images
ICIP'09: Proceedings of the 16th IEEE international conference on Image processing

Conventional relevance feedback schemes may not be suitable to all practical applications of content-based image retrieval (CBIR), since most ordinary users would like to complete their search in a single interaction, especially on the web search. In ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

SAC '01: Proceedings of the 2001 ACM symposium on Applied computing

March 2001

692 pages

ISBN:1581132875

DOI:10.1145/372202

Chairman:
G. B. Lamont
Air Force Institute of Technology

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 2001

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SAC01

Sponsor:

SIGAPP

SAC01: 2001 Symposium on Applied Computing

Nevada, Las Vegas, USA

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Upcoming Conference

SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
454
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 10 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Tungkasthan APremchaiswadi W(2011)Automatic region of interest detection in natural imagesProceedings of the 15th WSEAS international conference on Computers10.5555/2028299.2028380(437-444)Online publication date: 15-Jul-2011
https://dl.acm.org/doi/10.5555/2028299.2028380
Tungkatsathan APremchaiswadi WPremchaiswadi N(2010)Unsupervised Detection for Minimizing a Region of Interest around Distinct Object in Natural ImagesProceedings of the 2010 International Conference on Digital Image Computing: Techniques and Applications10.1109/DICTA.2010.45(202-207)Online publication date: 1-Dec-2010
https://dl.acm.org/doi/10.1109/DICTA.2010.45
Hiransakolwong N(2005)Automated liver detection in ultrasound imagesProceedings of the 4th international conference on Image and Video Retrieval10.1007/11526346_65(619-628)Online publication date: 20-Jul-2005
https://dl.acm.org/doi/10.1007/11526346_65
Vu KHua KJiang NLamont GHaddad HPapadopoulos GPanda B(2003)Improving image retrieval effectiveness in query-by-example environmentProceedings of the 2003 ACM symposium on Applied computing10.1145/952532.952685(774-781)Online publication date: 9-Mar-2003
https://dl.acm.org/doi/10.1145/952532.952685
Vu KHua KTavanapong W(2003)Image Retrieval Based on Regions of InterestIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2003.120902115:4(1045-1049)Online publication date: 1-Jul-2003
https://dl.acm.org/doi/10.1109/TKDE.2003.1209021
Hiransakolwong NHua KKhanh Vu Windyga P(2003)Segmentation of ultrasound liver images: an automatic approach2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)10.1109/ICME.2003.1220982(I-573)Online publication date: 2003
https://doi.org/10.1109/ICME.2003.1220982
Hiransakolwong NWindyga PHua KVu K(2002)FASU: a Full Automatic Segmenting System for Ultrasound imagesSixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings.10.1109/ACV.2002.1182163(90-94)Online publication date: 2002
https://doi.org/10.1109/ACV.2002.1182163

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Towards Interactive Image Query System for Content-Based Image Retrieval

An efficient semantic Related image retrieval method

Image retrieval based on bag of images