RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • SCOPUSKCI등재

        Fast Detection of Mura Defects Based on Modified Watershed Algorithm

        Ye Jian Zhang(장엽검),Hyonam Joo(주효남),Joon Seek Kim(김준식) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.6

        Many kinds of defects show up during the process of manufacturing display panels. However, mura defects are the most difficult to detect using the conventional image processing algorithms. Many factors cause mura defects to appear in display panels. When images are taken using cameras, mura defects normally show up as relatively dark or bright regions with no definite shape, no clear contours, and very low contrast against their surrounding background. When an imaged mura defect is relatively dark compared to its background, it can be considered a water catchment basin when the whole image is visualized in three dimensions (i.e., is topographically interpreted), and such catchment basins can be detected by watershed algorithms. In this paper, for the accurate segmentation of the mura region, the flooding step of the original watershed algorithm is carefully redesigned to detect the mura defect that exists both inside and at the boundary of an image. The depth of the catchment basins is recorded iteratively and then is used to segment the mura defects. The just noticeable difference (JND) technique is used to quantify the level of the mura defects. It is shown, by extensive experiments, that the proposed algorithm performs well, detecting very low-contrast mura defects, and quickly detects defects located anywhere in the image.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼