The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Rearranged DCT Feature Analysis Based on Corner Patches for CBIR (contents based image retrieval)

CBIR을 위한 코너패치 기반 재배열 DCT특징 분석

  • Lee, Jimin (A-joo Communications Inc. Research Institute.) ;
  • Park, Jongan (Dept. of Information and Communication Engineering Chosun University) ;
  • An, Youngeun (Dept. of Division of Undeclared Majors, Chosun University) ;
  • Oh, Sangeon (Dept. of Information and Communication Engineering Chosun University)
  • Received : 2016.10.26
  • Accepted : 2016.11.28
  • Published : 2016.12.01
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Abstract

In modern society, creation and distribution of multimedia contents is being actively conducted. These multimedia information have come out the enormous amount daily, the amount of data is also large enough it can't be compared with past text information. Since it has been increased for a need of the method to efficiently store multimedia information and to easily search the information, various methods associated therewith have been actively studied. In particular, image search methods for finding what you want from the video database or multiple sequential images, have attracted attention as a new field of image processing. Image retrieval method to be implemented in this paper, utilizes the attribute of corner patches based on the corner points of the object, for providing a new method of efficient and robust image search. After detecting the edge of the object within the image, the straight lines using a Hough transformation is extracted. A corner patches is formed by defining the extracted intersection of the straight line as a corner point. After configuring the feature vectors with patches rearranged, the similarity between images in the database is measured. Finally, for an accurate comparison between the proposed algorithm and existing algorithms, the recall precision rate, which has been widely used in content-based image retrieval was used to measure the performance evaluation. For the image used in the experiment, it was confirmed that the image is detected more accurately in the proposed method than the conventional image retrieval methods.

Keywords

References

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