Efficient object identification and localization for image retrieval using query-by-regionopen access
- Authors
- Lee, Yong-Hwan; Kim, Bonam; Kim, Heung-Jun
- Issue Date
- Jan-2012
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Object localization; Correlogram back-projection; Object region detection; Query-by-subregion; Region-based image retrieval
- Citation
- COMPUTERS & MATHEMATICS WITH APPLICATIONS, v.63, no.2, pp 511 - 517
- Pages
- 7
- Indexed
- SCI
SCIE
SCOPUS
- Journal Title
- COMPUTERS & MATHEMATICS WITH APPLICATIONS
- Volume
- 63
- Number
- 2
- Start Page
- 511
- End Page
- 517
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/22396
- DOI
- 10.1016/j.camwa.2011.08.019
- ISSN
- 0898-1221
1873-7668
- Abstract
- Localizing an object within an image is a common task in the field of computer vision, and represents the first step towards the solution of the recognition problem. This paper presents an efficient approach to object localization for image retrieval using query-by-region. The new algorithm utilizes correlogram back-projection in the YCbCr chromaticity components to handle the problem of subregion querying. Utilizing similar spatial color information enables users to detect and locate primary location and candidate regions accurately without the need for further information about the number of objects. Comparing this new approach to existing methods, an improvement of 21% was observed in experimental trials. These results reveal that color correlograms are markedly more effective than color histograms for this task. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.
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