Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Index-based Boundary Matching Supporting Partial Denoising for Large Image Databases

  • Kim, Bum-Soo (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology)
  • Received : 2019.09.18
  • Accepted : 2019.10.07
  • Published : 2019.10.31
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Abstract

In this paper, we propose partial denoising boundary matching based on an index for faster matching in very large image databases. Attempts have recently been made to convert boundary images to time-series with the objective of solving the partial denoising problem in boundary matching. In this paper, we deal with the disk I/O overhead problem of boundary matching to support partial denoising in a large image database. Although the solution to the problem superficially appears trivial as it only applies indexing techniques to boundary matching, it is not trivial since multiple indexes are required for every possible denoising parameters. Our solution is an efficient index-based approach to partial denoising using $R^*-tree$ in boundary matching. The results of experiments conducted show that our index-based matching methods improve search performance by orders of magnitude.

본 논문에서는 대용량 이미지 데이터베이스에서 보다 빠른 매칭을 위한 색인 기반의 부분 노이즈 제거 윤곽선 매칭을 제안한다. 최근에는 윤곽선 매칭에서 부분 노이즈제거 문제를 해결하기 위해 윤곽선 이미지를 시계열로 변환하는 시도가 있어 왔다. 본 논문에서는 대용량 이미지 데이터베이스에서 부분 노이즈제거를 지원하기 위해 윤곽선 매칭의 디스크 I/O 오버헤드 문제를 다룬다. 이는 색인 기술을 윤곽선 매칭에 단순히 적용하면 되기 때문에 단순해 보이지만 가능한 모든 노이즈제거 매개변수에 대해 여러 개의 색인이 필요하기 때문에 어려운 문제이다. 이 문제를 해결하기 위해 본 논문에서는 윤곽선 매칭에서 $R^*-tree$를 사용하여 부분 노이즈제거에 대한 효율적인 색인 기반 접근 방식을 제안한다. 수행 된 실험 결과, 제안한 색인 기반 매칭 방법은 검색 성능을 수백 배 향상시킨다.

Keywords

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