Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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Inspection of Vehicle Headlight Defects

차량 헤드라이트 불량검사 방법

  • 김근홍 (금오공과대학교 컴퓨터IT학과, 프로텍 코퍼레이션) ;
  • 문창배 (금오공과대학교 ICT융합특성화연구센터) ;
  • 김병만 (금오공과대학교 컴퓨터소프트웨어공학과) ;
  • 오득환 (금오공과대학교 컴퓨터소프트웨어공학과)
  • Received : 2018.01.16
  • Accepted : 2018.02.27
  • Published : 2018.02.28
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Abstract

In this paper, we propose a method to determine whether there is a defect by using the similarity between ROIs (Region of Interest) of the standard image and ROIs of the image which is corrected in position and rotation after capturing the vehicle headlight. The degree of similarity is determined by the template matching based on the histogram of image, which is a some modification of the method provided by OpenCV where template matching is performed on the raw image not the histogram. The proposed method is compared with the basic method of OpenCV for performance analysis. As a result of the analysis, it was found that the proposed method showed better performance than the OpenCV method, showing the accuracy close to 100%.

본 논문에서는 차량 헤드라이트의 불량 유무를 판별하기 위하여 생산된 헤드라이트 이미지를 위치 및 회전 보정 후 검사이미지의 ROI(Region of Interest)와 표준 이미지의 ROI와의 유사도를 이용하여 불량 유무를 판단하는 방법을 제안하였다. 유사도 판별은 OpenCV에서 제공하는 템플릿매칭 유사도 판별방법을 응용하여 히스토그램 기반에서 유사도를 판별하는 방법을 사용하였고, 성능 분석을 목적으로 기존 OpenCV의 기본 방법과 비교하였다. 분석결과, OpenCV의 기본 방법보다 좋은 성능을 보임을 알 수 있었고, 제안 방법의 경우 불량 판별율 100%에 근접함을 알 수 있었다.

Keywords

References

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