Efficient object identification and localization for image retrieval using query-by-region

Authors:
Yong-Hwan Lee;Bonam Kim;Heung-Jun Kim
Affiliations:
Dankook University, Yongin, Republic of Korea;Chungnam National University, Daejon 448-701, Republic of Korea;Gyeongnam National University of Science and Technology, JinJu, Republic of Korea
Venue:
Computers & Mathematics with Applications
Year:
2012

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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.