• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.55-63
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• 2011

Having a wide angle of view, a fisheye lens is useful for obtaining images of the inside wall of a tunnel. A circular fisheye tunnel image can be transformed into a familiar rectangular image by applying the concept of cylindrical projection. This projection transformation causes several types of distortions in the projected image. This paper discusses the distortion on the boundary lines between smoothly curved wall and flat ground. We analyzed the cause of this boundary distortion, developed transformation model, and derived a correction formular. A distortion correction software programmed in Visual C++ applied to projected image. Consequently, boundary-corrected image could be obtained. Research into other distortions of projected image will helpful in obtaining tunnel image that resembles real tunnel from fisheye tunnel image.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.30-42
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• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.105-111
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• 2009

A construction can be more convenient and safer with adequate informations. Consequently, studies on collecting various informations using newest surveying technology and applying these informations to a construction have been making progress recently. Digital images are easy to obtain and contain various informations. Therefore, with the recent development of image processing technology, the application field of digital images is getting wider. In this study, we proposed to use a fisheye lens camera in underground construction sites, especially tunnels, to overcome inconvenience in photographing with general lens cameras. A program for mapping the surface of a tunnel and making a mosaic image is also developed. This mosaic image can be applied to observe and analyze abnormal phenomenons on tunnel surface like cracks, water leakage, exfoliates, and so on.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.181-184
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• 2004

본 논문을 통하여 개발된 시스템은 라인카메라를 사용하여 터널의 균열 영상을 획득하기 위하여 사용되는 시스템으로, 터널 내부의 균열 영상을 실시간으로 촬영하여 저장하는 시스템이다. 터널 영상은 의료영상과 같이 작은 손실에도 큰 영향을 미칠 수 있다. 이러한 요소 때문에 본 시스템에서는 CCD 방식의 라인 스캔 카메라를 이용하여 터널 영상을 촬영하며, 이를 저장 하는 방법에 있어서는 비손실 압축기법을 사용하였다. 비손실 압축 기법의 사용을 이용하여 영상을 저장하는 방식은 많은 데이터 저장공간을 필요로 한다. 이러한 문제점은 기술 개발의 놀라운 성장과 더불어 기존 테이프 기반의 방식에서 벗어나 로컬 하드디스크로 직접 저장하는 기법을 사용할 수 있게 되었다. 즉, 라인 카메라를 이용하는 기존 시스템의 경우에는 영상데이타를 실시간으로 저장할 수 없는 문제점 때문에 촬영 속도를 느리게 하면서 영상을 획득하였으며, 획득한 영상을 테이프로 저장하도록 설계되었다. 이에 반하여 본 시스템에서는 테이프를 대신하여 로컬 디스크를 사용하여, 대용량의 영상을 실시간으로 저장할 수 있는 시스템을 개발하였다. 예비실험을 통하여 나타난 결과에 따르면 본 논문을 통하여 개발된 시스템은 약 20Km 이상의 속도로 진행하는 열차에서 터널의 영상을 실시간으로 촬영하여 저장할 수 있음을 살펴볼 수 있었다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6089-6097
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• 2012

This study suggested a method of detecting an incident inside tunnel by using camera that is installed within the tunnel. As for the proposed incident detection method, a static object, travel except vehicles, smoke, and contra-flow were detected by extracting the moving object through using the real-time background image differencing after receiving image from the camera, which is installed inside the tunnel. To detect the moving object within the tunnel, the positive background image was created by using the moving information of the object. The incident detection method was developed, which is strong in a change of lighting that occurs within the tunnel, and in influence of the external lighting that occurs in the entrance and exit of the tunnel. To examine the efficiency of the suggested method, the experimental images were acquired from Marae tunnel and Expo tunnel in Yeosu of Jeonnam and from Unam tunnel in Imsil of Jeonbuk. Number of images, which were used in experiment, included 20 cases for static object, 20 cases for travel except vehicles, 4 cases for smoke, and 10 cases for contra-flow. As for the detection rate, all of the static object, the travel except vehicles, and the contra-flow were detected in the experimental image. In case of smoke, 3 cases were detected. Thus, excellent performance could be confirmed. The proposed method is now under operation in Marae tunnel and Expo tunnel in Yeosu of Jeonnam and in Unam tunnel in Imsil of Jeonbuk. To examine accurate efficiency, the evaluation of performance is considered to be likely to be needed after acquiring the incident videos, which actually occur within tunnel.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2010.10a
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• pp.155-158
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• 2010

본 연구에서는 최근 도심지 대심도 지하도로 및 침매터널등에서 중요성이 부각되고 있는 터널내 화재안전 설계를 위한 영상유고감지시스템의 성능평가를 수행하였다. 영상유고감지시스템(VIDS)의 성능 평가를 위하여 터널 내부에서 발생할 수 있는 유고상황을 5가지로 구분하여 보행자, 낙하물, 정지차량, 역주행, 연기발생등의 상황을 인위적으로 발생시켰으며 이에 따른 감지 능력을 평가하였다. 실험결과 2, 3회 걸친 지속적인 교정과 세부조정을 거친 후에는 보행자 98.3%, 낙하물 96.7%, 정지차량 100%, 역주행 100%, 연기감지 100%의 감지율을 나타내었으며 카메라의 설치거리 100m 이내에서 비교적 높은 감지율을 나타내었다. 영상유고감지기의 적용 신뢰도는 터널내 조도, 카메라의 설치 위치에 따른 영상 변화등에 의존적이었으나 대심도 터널등의 신속한 화재감지를 위한 대안으로 적용될 수 있을 것으로 판단되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1082-1087
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• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.