Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Image-based Image Retrieval System Using Duplicated Point of PCA-SIFT

PCA-SIFT의 차원 중복점을 이용한 이미지 기반 이미지 검색 시스템

  • Choi, GiRyong (Department of Computer Engineering, Sungkyunkwan University) ;
  • Jung, Hye-Wuk (Department of Computer Engineering, Sungkyunkwan University) ;
  • Lee, Jee-Hyoung (Department of Computer Engineering, Sungkyunkwan University)
  • 최기룡 (성균관대학교 컴퓨터공학과) ;
  • 정혜욱 (성균관대학교 컴퓨터공학과) ;
  • 이지형 (성균관대학교 컴퓨터공학과)
  • Received : 2012.10.06
  • Accepted : 2013.04.10
  • Published : 2013.06.25
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Abstract

Recently, as multimedia information becomes popular, there are many studies to retrieve images based on images in the web. However, it is hard to find the matching images which users want to find because of various patterns in images. In this paper, we suggest an efficient images retrieval system based on images for finding products in internet shopping malls. We extract features for image retrieval by using SIFT (Scale Invariant Feature Transform) algorithm, repeat keypoint matching in various dimension by using PCA-SIFT, and find the image which users search for by combining them. To verify efficiency of the proposed method, we compare the performance of our approach with that of SIFT and PCA-SIFT by using images with various patterns. We verify that the proposed method shows the best distinction in the case that product labels are not included in images.

최근 멀티미디어 정보가 보편화됨에 따라 인터넷에서 이미지를 기반으로 정보를 검색하려는 다양한 시도가 진행되고 있다. 그러나 이미지에는 다양한 패턴이 포함되어 있기 때문에 정확하게 원하는 이미지를 찾는 것은 아직 어려움이 많다. 본 논문에서는 인터넷 쇼핑몰의 상품검색을 효율적으로 할 수 있는 이미지 기반 검색 시스템을 제안한다. 제안된 검색 방법은 SIFT(Scale Invariant Feature Transform) 알고리즘을 이용하여 이미지 검색을 위한 특징을 추출하고, PCA-SIFT를 이용하여 여러 차원에서 키포인트의 매칭을 반복하여 누적 후 사용자가 원하는 상품을 찾아준다. 제안된 방법의 효율성을 검증하기 위해, 다양한 패턴의 상품 이미지를 이용하여 기존 SIFT, PCA-SIFT 방법과 제안된 방법을 비교한 결과, 상표가 포함되지 않은 이미지의 경우 제안방법이 가장 높은 변별력을 보였으며, 효과적인 이미지 검색의 가능성을 보였다.

Keywords

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