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

Korean Society of Computer Information (한국컴퓨터정보학회)
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Filtering Feature Mismatches using Multiple Descriptors

다중 기술자를 이용한 잘못된 특징점 정합 제거

  • Kim, Jae-Young (School of Electrical Engineering, University of Ulsan) ;
  • Jun, Heesung (School of Electrical Engineering, University of Ulsan)
  • Received : 2013.11.15
  • Accepted : 2013.12.19
  • Published : 2014.01.29
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Abstract

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.

이미지 기술자(descriptor)를 이용한 정합은 최근까지 컴퓨터 비전과 패턴인식 분야에서 사용되고 있는 강력한 정합 방법이다. 그러나 3차원 시점이 변화되거나 밝기가 변화된 이미지, 반복된 패턴이 포함된 이미지 등에서 잘못된 정합들이 발생한다. 본 논문에서는 반복된 패턴이 포함되어 있는 이미지에서 잘못된 정합들이 많이 발생하는 문제점에 대해 기술하고 이를 분석하여 잘못된 정합들을 제거할 수 있는 방법을 제안한다. MDMF(Multiple Descriptors-based Mismatch Filtering) 방법은 각 특징점에 대해 인접한 여러 개의 특징점들의 기술자들을 사용하여 다중 기술자를 생성한 후 이를 활용하여 잘못된 정합들을 제거한다. 실험에서는 크기 변환, 회전 변환, 어파인 변환에 대해 기존 SIFT와 ASIFT의 정합율을 MDMF를 이용해 제거한 정합율과 비교하여 MDMF가 잘못된 정합을 성공적으로 제거할 수 있음을 보였다.

Keywords

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