• Journal of the Institute of Electronics Engineers of Korea TC
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• 제43권9호
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• pp.69-79
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• 2006

A number of researches on vision-based traffic monitoring system have been carried out. Most of traffic monitoring schemes belong to one of two categories: analyzing of entire traffic scene and examining of local region. However, the proposed methods suffer from severe performance deterioration when applied in different operating conditions because of the loss of robustness. This paper is aimed at surveying various methods proposed and analyzing the advantages and disadvantages of these methods. Also we propose and investigate appropriate approaches to solve the problems in specific applications.

• Ocean and Polar Research
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• 제28권2호
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• pp.209-214
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• 2006

The East Sea Branch (ESB) of KORDI will be launched in 2008. She will take a role of monitoring the sea surface topography and temperature by satellites, short- and long-term sea levels by tide gauges, coastal currents and open-sea circulation by setting up coastal radars and mooring current-meters and acoustic equipments, as well as monitoring nearshore processes, coastal erosion and water pollution. A basic program of coastal zone management will help ocean-policy makers to set up right decisions based upon scientific background of the regional data in the East Sea. Networking among the neighboring countries around the sea will supply more useful information not only for experts but also for ordinary vacationers or fishermen. In order for this program to be successfully settled down during the next decade, it is necessary for a leader to have the right vision to attract more experts from global brain pools and to manage the ESB as a leading-edge observatory in the world. Details about this leading-edge operational program are introduced in the text.

• Proceedings of the KSR Conference
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1483-1487
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• 2006

In electric railway, image monitoring using high speed camera provides reliable, timely information of wear and geometry status, important in taking decisions for overhead contact wire maintenance. The contribution of this research is the development of a simple real-time monitoring system for use in measurement subsystem of contact wire and geometry of overhead contact wire in electric railway. The system has been consists of a high speed CMOS camera with resolution $1024{\times}1280$ pixels, line type laser source and PC-based image acquisition system with PCI Express slot. Vision acquisition software have been used in application programming interface for image acquisition, display, and storage with a frequency of sampling of 500 acquisitions per second.

• Proceedings of the KWS Conference
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.307-313
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• 2002

This paper describes a weld pool monitoring technique, which is based on the weld pool image analysis. The proposed image analysis algorithm uses machine vision techniques to extract geometrical information from the weld pool image such as maximum weld pool width, gap width and misalignment between the joint longitudinal axis and the welding wire. These can be related to the welding parameters (welding voltage and current, wire feed speed and standoff) to produce control actions necessary to ensure that the required weld quality will be achieved. The experiments have shown that the algorithm is able to produce good estimates of the weld pool geometry; however, the adjustment of the camera parameters affects the image quality and, consequently, has a great influence over the estimation.

• Structural Monitoring and Maintenance
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• 제7권1호
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• pp.59-67
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• 2020

This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

• Journal of the Semiconductor & Display Technology
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• 제10권2호
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.155-174
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• 2023

High performance concrete (HPC) has been extensively used in thin overlay for repair purpose due to its excellent strength and durability. This paper presents an experiment, where the sensor-instrumented HPC overlays have been followed by dynamic strain and moisture content monitoring for 1 year, under normal traffic. The vibrating wire and soil moisture sensors were embedded in overlay before construction. Four given HPC mixes (2 original mixes and their shrinkage-modified mixes) were used for overlays to contrast the strain and moisture results. A calibration method to accurately measure the moisture content for a given concrete mixture using soil moisture sensor was established. The monitoring results indicated that the modified mixes performed much better than the original mixes in shrinkage cracking control. Weather condition and concrete maturity at early age greatly affected the strain in concrete. The strain in HPC overlay was primarily in longitudinal direction, leading to transverse cracks. Additionally, the most moisture loss in concrete occurred at early age. Its rate was very dependent on weather. After one year, cracking survey was carried out by vision to verify the strain direction and no cracks observed in shrinkage modified mixes.

• International conference on construction engineering and project management
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• Smart Structures and Systems
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• 제32권4호
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• pp.207-218
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• 2023

Real-time monitoring of the behavior of reinforced soil retaining wall (RSW) is required for safety checks. In this study, a targetless displacement measurement technology (TDMT) consisting of an image registration module and a displacement calculation module was proposed to monitor the behavior of RSW, in which facing displacement and settlement typically occur. Laboratory and field experiments were conducted to compare the measuring performance of natural target (NT) with the performance of artificial target (AT). Feature count- and location-based performance metrics and displacement calculation performance were analyzed to determine their correlations. The results of laboratory and field experiments showed that the feature location-based performance metric was more relevant to the displacement calculation performance than the feature count-based performance metric. The mean relative errors of the TDMT were less than 1.69 % and 5.50 % for the laboratory and field experiments, respectively. The proposed TDMT can accurately monitor the behavior of RSW for real-time safety checks.

• Korean Journal of Construction Engineering and Management
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• 제21권5호
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• pp.11-19
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• 2020

A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.