Journal of Korean Tunnelling and Underground Space Association (한국터널지하공간학회 논문집)

Korean Tunnelling and Underground Space Association (한국터널지하공간학회)
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Analysis of the application of image quality assessment method for mobile tunnel scanning system

이동식 터널 스캐닝 시스템의 이미지 품질 평가 기법의 적용성 분석

  • Chulhee Lee (Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology) ;
  • Dongku Kim (Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology) ;
  • Donggyou Kim (Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology)
  • 이철희 (한국건설기술연구원 지반연구본부) ;
  • 김동구 (한국건설기술연구원 지반연구본부) ;
  • 김동규 (한국건설기술연구원 지반연구본부)
  • Received : 2024.06.26
  • Accepted : 2024.07.12
  • Published : 2024.07.31
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Abstract

The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

인력기반의 점검보다 안전하고 효율적인 자동화 점검을 위하여 스캐닝 기술 개발이 가속화되고 있다. 컴퓨터비전 기술을 활용하여 수집된 이미지로부터 시설물 손상을 자동으로 검출하는 연구도 증가하고 있다. 이미지의 픽셀 크기, 품질 및 수량은 손상 자동 검출을 위한 딥러닝이나 이미지 처리 성능에 영향을 미칠 수 있다. 본 연구는 딥러닝기반 손상 자동 검출을 위한 이동식 터널 스캐닝 시스템의 카메라 성능과 고품질의 원시 이미지 데이터 취득을 위한 기초연구로, 이미지의 품질을 정량적으로 평가하기 위한 기법을 제안하려고 한다. 40 km/h의 이동속도 모사가 가능한 패널 장치에 테스트차트를 부착하고 국제표준 ISO 12233방법으로 실내시험을 수행하였다. 기존의 이미지 품질 평가기법들을 적용하여 실내실험에서 얻어진 이미지의 품질을 평가하였다. 카메라의 셔터스피드는 이미지에 발생하는 모션블러와 밀접한 관련이 있는 것으로 판단되었다. 이미지 품질 평가 기법 중 하나인 modulation transfer function (MTF)는 이미지 품질을 객관적으로 평가할 수 있으며, 시각적 관찰과 일치하는 것으로 판단되었다.

Keywords

Acknowledgement

본 연구는 국토교통과학기술진흥원의 기반시설 첨단관리(total care) 기술개발사업(RS-2022-00142566)의 지원으로 수행되었습니다. 이에 감사드립니다.

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