• Title/Summary/Keyword: 터널영상

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A System to Recognize Position of Moving Vehicle based on Images (영상을 이용한 차량의 주행 위치 측정 시스템)

  • Kim, Jin-Deog;Moon, Hye-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.12
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    • pp.2619-2625
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    • 2011
  • The GPS technique widely used recently in car navigation system has two problems that are unavailability in urban canyons and inherent positional error rate. The one has been studied and solved in many literatures. However, the other still leads to incorrect locational information in some area, especially parallel roads. This paper proposes and implements a system to recognize lane of moving vehicle based on images obtained from in-vehicle networks or other devices. The proposed system utilizes a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. It also employs a method for accuracy improvement. The results obtained from experimental test on real-time navigation show that the proposed systems works well and the accuracy increases.

Implementation of Image Security System for CCTV Using Analysis Technique of Color Informations (색 정보 분석 기법을 이용한 효율적인 CCTV 영상 보안 시스템의 구현)

  • Ryu, Su-Bong;Kang, Min-Sup
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.5
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    • pp.219-227
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    • 2012
  • This paper describes the design and implementation of an efficient image security system for CCTV using the analysis technique of color informations. In conventional approaches, the compression and encryption techniques are mainly used for reducing the data size of the original images while the analysis technique of color information is first proposed, which eliminates the overlapping part of the original image data in our approach. In addition, security-enhanced CCTV image security system is presented using SSL/VPN tunneling technique. When we use the method proposed in this paper, an efficient image processing is enable for a mount of information, and also security problem is enhanced. Through the implementation results, the proposed method showed that the original image information are dramatically reduced.

Analysis on Freezing Reduction of Road Tunnels with Heat Insulation Method during Winter (단열공법이 적용된 겨울철 도로터널의 동결저감 효과 분석)

  • Son, Hee-Su;Jun, Kyoung-Jea;Yune, Chan-Young
    • Journal of the Korean Geotechnical Society
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    • v.33 no.8
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    • pp.17-27
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    • 2017
  • Gangwon province which is located in northeast of Korea is the coldest region where average daily temperature is below zero during winter while the other regions are above zero. However, there have been insufficient researches on the insulation design and the effect of the insulation on the freezing damages, even though freezing damages were reported consistently in the lining of road tunnel during winter. In this study, to investigate the effect of insulations on the reduction of freezing damages, numerical analysis was performed considering geotechnical and meteorological characteristics in Gangwon province during winter. As a result, it was found that thickness of concrete and shotcrete in lining had negligible effect on the freezing depth while the insulation had significant effect on it. In addition, because the freezing depth is greatly affected by the thermal conductivity of the ground behind the lining in the period of cold weather, these effects should be considered in the estimation of the insulation thickness.

Acoustic Signal-Based Tunnel Incident Detection System (음향신호 기반 터널 돌발상황 검지시스템)

  • Jang, Jinhwan
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.5
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    • pp.112-125
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    • 2019
  • An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s.

Adversarial learning for underground structure concrete crack detection based on semi­supervised semantic segmentation (지하구조물 콘크리트 균열 탐지를 위한 semi-supervised 의미론적 분할 기반의 적대적 학습 기법 연구)

  • Shim, Seungbo;Choi, Sang-Il;Kong, Suk-Min;Lee, Seong-Won
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.22 no.5
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    • pp.515-528
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    • 2020
  • Underground concrete structures are usually designed to be used for decades, but in recent years, many of them are nearing their original life expectancy. As a result, it is necessary to promptly inspect and repair the structure, since it can cause lost of fundamental functions and bring unexpected problems. Therefore, personnel-based inspections and repairs have been underway for maintenance of underground structures, but nowadays, objective inspection technologies have been actively developed through the fusion of deep learning and image process. In particular, various researches have been conducted on developing a concrete crack detection algorithm based on supervised learning. Most of these studies requires a large amount of image data, especially, label images. In order to secure those images, it takes a lot of time and labor in reality. To resolve this problem, we introduce a method to increase the accuracy of crack area detection, improved by 0.25% on average by applying adversarial learning in this paper. The adversarial learning consists of a segmentation neural network and a discriminator neural network, and it is an algorithm that improves recognition performance by generating a virtual label image in a competitive structure. In this study, an efficient deep neural network learning method was proposed using this method, and it is expected to be used for accurate crack detection in the future.

Development of an Accident detection system using a scanner (스캐너를 이용한 유고 감지 시스템 개발)

  • Jeong, Yang-Kwon;Kim, Yong-Sik;Kim, Jin-Seok;Hui, Xue-Wu
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.2
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    • pp.457-463
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    • 2012
  • Changing the environment around detecting areas may lower the performance of a video-based accident detection system. Region of interest(ROI) and background information changing constantly on account of the car headlights at night and a sudden changes in the weather are the biggest factors to increase the ratio of wrong results. Thus, we proposed and implemented the integrated accident detection system combined the video-based system and the laser-based imaging system. In this paper, we were able to overcome the majority problem of video-based system and it was a meaningful results that it can improve the reliability for the system.

Estimation of Blast Fragmentation using Stereophotogrammetry (입체사진측량기법을 이용한 파쇄도 추정)

  • Han, Jeong-Hun;Song, Jae-Joon;Jo, Young-Do
    • Tunnel and Underground Space
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    • v.21 no.1
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    • pp.82-92
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    • 2011
  • Stereophotogrammetry is used to extract spatial information of an object by constructing a stereo-image from two or more photos. In this study, stereophotogrammetry was adopted for analyzing blast fragmentation of rock blocks in a quarry site. 2D image processing and stereophotogrammetry were applied to the fragmentation analysis of rock blocks horizontally scattered in a laboratory, and their results were compared with physical measurements using a water tank. Fragmentation of rock muckpiles was estimated in laboratory and field tests by using the stereophotogrammetry and statistical analysis.

Deep Image Retrieval using Attention and Semantic Segmentation Map (관심 영역 추출과 영상 분할 지도를 이용한 딥러닝 기반의 이미지 검색 기술)

  • Minjung Yoo;Eunhye Jo;Byoungjun Kim;Sunok Kim
    • Journal of Broadcast Engineering
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    • v.28 no.2
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    • pp.230-237
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    • 2023
  • Self-driving is a key technology of the fourth industry and can be applied to various places such as cars, drones, cars, and robots. Among them, localiztion is one of the key technologies for implementing autonomous driving as a technology that identifies the location of objects or users using GPS, sensors, and maps. Locilization can be made using GPS or LIDAR, but it is very expensive and heavy equipment must be mounted, and precise location estimation is difficult for places with radio interference such as underground or tunnels. In this paper, to compensate for this, we proposes an image retrieval using attention module and image segmentation maps using color images acquired with low-cost vision cameras as an input.

An Algorithm for Traffic Information by Vehicle Tracking from CCTV Camera Images on the Highway (고속도로 CCTV카메라 영상에서 차량 추적에 의한 교통정보 수집 알고리즘)

  • Min Joon-Young
    • Journal of Digital Contents Society
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    • v.3 no.1
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    • pp.1-9
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    • 2002
  • This paper is proposed to algorithm for measuring traffic information automatically, for example, volume count, speed and occupancy rate, from CCTV camera images installed on highway, add to function of image detectors which can be collected the traffic information. Recently the method of traffic informations are counted in lane one by one, but this manner is occurred critical errors by occlusion frequently in case of passing larger vehicles(bus, truck etc.) and is impossible to measure in the 8 lanes of highway. In this paper, installed the detection area include with all lanes, traffic informations are collected using tracking algorithm with passing vehicles individually in this detection area, thus possible to detect all of 8 lanes. The experiment have been conducted two different real road scenes for 20 minutes. For the experiments, the images are provided with CCTV camera which was installed at Kiheung Interchange upstream of Kyongbu highway, and video recording images at Chungkye Tunnel. For image processing, images captured by frame-grabber board 30 frames per second, $640{\times}480$ pixels resolution and 256 gray-levels to reduce the total amount of data to be interpreted.

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Prediction of Ground Condition and Evaluation of its Uncertainty by Simulated Annealing (모의 담금질 기법을 이용한 지반 조건 추정 및 불확실성 평가에 관한 연구)

  • Ryu Dong-Woo
    • Tunnel and Underground Space
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    • v.15 no.4 s.57
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    • pp.275-287
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    • 2005
  • At the planning and design stages of a development of underground space or tunneling project, the information regarding ground conditions is very important to enhance economical efficiency and overall safety In general, the information can be expressed using RMR or Q-system and with the geophysical exploration image. RMR or Q-system can provide direct information of rock mass in a local scale for the design scheme. Oppositely, the image of geophysical exploration can provide an exthaustive but indirect information. These two types of the information have inherent uncertainties from various sources and are given in different scales and with their own physical meanings. Recently, RMR has been estimated in unsampled areas based on given data using geostatistical methods like Kriging and conditional simulation. In this study, simulated annealing(SA) is applied to overcome the shortcomings of Kriging methods or conditional simulations just using a primary variable. Using this technique, RMR and the image of geophysical exploration can be integrated to construct the spatial distribution of RM and to evaluate its uncertainty. The SA method was applied to solve an optimization problem with constraints. We have suggested the practical procedure of the SA technique for the uncertainty evaluation of RMR and also demonstrated this technique through an application, where it was used to identify the spatial distribution of RMR and quantify the uncertainty. For a geotechnical application, the objective functions of SA are defined using statistical models of RMR and the correlations between RMR and the reference image. The applicability and validity of this application are examined and then the result of uncertainty evaluation can be used to optimize the tunnel layout.