• 제목/요약/키워드: $\alpha$-Least Trimmed Square

검색결과 3건 처리시간 0.022초

효과적인 영상처리를 위한 α-LTSHD 기반의 FCNN 구조 연구 (A study on FCNN structure based on a α-LTSHD for an effective image processing)

  • 변오성;문성룡
    • 한국지능시스템학회논문지
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    • 제12권5호
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    • pp.467-472
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    • 2002
  • 본 논문에서, 영상에서 임펄스 잡음을 효과적으로 제거하고, 연산 속도를 개선하기 위해 Fuzzy Cellular Neural Network(FCNN)구조에 Hausdorff distance(HD)를 적용한 $\alpha$-Least Trimmed Square HD($\alpha$-LTSHD) 기반 FCNN 구조를 제안한다. FCNN는 Cellular Neural Network(CNN) 구조에 퍼지 이론을 적용한 것이고, HD는 특징 대상의 대응 없이 이진 영상의 두 픽셀 집합 사이의 거리를 구하는 척도로 물체의 정합에 널리 사용한다. 성능 평가를 위해, 제안된 방법을 MSE와 SNR을 이용하여 기존 FCNN, Opening-Closing(OC) 그리고 LTSHD 연산자를 적용한 FCNN과 비교 분석하였다. 그 결과, 본 논문에서 제안된 망(network) 구조의 성능이 다른 필터보다 임펄스 잡음 제거에 우수함을 확인하였다.

Study on ${\alpha}-LTS$ Hausdorff distance applying ${\alpha}-trimmed$

  • Byun, Oh-Sung;Beak, Deok-Soo;Moon, Sung-Ryong
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.50-53
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    • 2000
  • It is effectively removed noise in the image using FCNN(Fuzzy Cellular Neural Network) applying fuzzy theory to CNN(Cellular Neural Network) structure and HD(Hausdorff Distance) commonly used measures for object matching. HD calculates the distance between two point set of pixels in two-dimensional binary images without establishing correspondence. Also, this method is proposed in order to improve the operation speed. In this paper, $\alpha$-LTSHD(Least Trimmed Square HD) operator applying $\alpha$-Trimmed to LTSHD, one field of HD, is applied to FCNN structure, and it is proposed as the modified method in order to remove noise in the image. Also, it is made a comparison with the other filters by using MSE and SNR after removing noise using the FCNNS which are applied $\alpha$-LTSHD operator through the computer simulation. In a result, FCNN performance which is applied the proposed $\alpha$-LTSHD demonstrated the superiority to the other filters in the noise removal.

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Robust hausdorff 거리 척도를 이용한 물체 정합 알고리듬 (Object matching algorithms using robust hausdorff distance measure)

  • 권오규;심동규;박래홍
    • 전자공학회논문지S
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    • 제34S권11호
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    • pp.93-101
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    • 1997
  • A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

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