Object Identification and Localization for Image Recognition

이미지 인식을 위한 객체 식별 및 지역화

  • Lee, Yong-Hwan (Dept. of Applied Computer Engineering, Dankook University) ;
  • Park, Je-Ho (Dept. of Computer Science, Dankook University) ;
  • Kim, Youngseop (Dept. of Electronic Engineering, Dankook University)
  • 이용환 (단국대학교 응용컴퓨터공학과) ;
  • 박제호 (단국대학교 컴퓨터과학과) ;
  • 김영섭 (단국대학교 전자공학과)
  • Received : 2012.12.05
  • Accepted : 2012.12.18
  • Published : 2012.12.31

Abstract

This paper proposes an efficient method of object identification and localization for image recognition. The new proposed algorithm utilizes correlogram back-projection in the YCbCr chromaticity components to handle the problem of sub-region querying. Utilizing similar spatial color information enables users to detect and locate primary location and candidate regions accurately, without the need for additional information about the number of objects. Comparing this proposed algorithm to existing methods, experimental results show that improvement of 21% was observed. These results reveal that color correlogram is markedly more effective than color histogram for this task. Main contribution of this paper is that a different way of treating color spaces and a histogram measure, which involves information on spatial color, are applied in object localization. This approach opens up new opportunities for object detection for the use in the area of interactive image and 2-D based augmented reality.

Keywords

References

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