Today, as the social demand for tap water safety and the need for an ICT-based intelligent integrated control system increase, K-water (Korea Water Resources Corporation) is building and operating a ‘Water pipe monitoring CCTV system’ to quickly respond to crises in the event of a water leak. However, in the case of the existing system, when the CCTV rotates, the image information and the mapped water pipe image do net match, so the operator has the limitation that the water pipe image must be mapped anew every time. In this paper, in odert to solve the above problems, we propose an improved system that can extract feature points from CCTV images, detect changes in the coordinate values of the feature points, and automatically transform the location of the water pipe image by utilizing LoFTR (Detector-Free Local Feature Matching with Transformer), a type of deep learning image matching algorithm that is actively being studied in th field of the latest computer vision, and examine its effectiveness.

ABSTRACT
1. 서 론
2. 관련연구
    2.1 CCTV영상 분석을 위한 특징점 매칭 알고리즘
    2.2 LoFTR(Local Feature Transformer) 알고리즘
    2.3 객체 탐지 알고리즘 성능평가 방법
3. 연구방법
    3.1 시스템 아키텍처
    3.2 데이터셋 및 전처리
    3.3 모델 학습 및 구현
4. 결과 및 고찰
5. 결 론
References

• 오승헌(성균관대학교 글로벌스마트시티융합학과) | Seung-Heon Oh (Department of Global Smart City, Sungkyunkwan University)
• 박승희(성균관대학교 건설환경공학부) | Seung-Hee Park (Department of Construction and Environmental Engineering, Sungkyunkwan University) Corresponding author