• Transactions of Materials Processing
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• v.8 no.3
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• pp.294-305
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• 1999

A vision-based surface-strain measurement system has been still improved since the authors devel-oped the first version of it. New algorithms for the subpixel measurement and surface smoothing are introduced to improve the accuracy and precision in the present study. The effects of these algorithms are investigated by error analysis. And the equations required to calculate 3D surface-strain of a shell element are derived from the shape function of a linear solid finite-element. The influences of external factors on the measurement error are also examined, and several trials are made to obtain possible optimal condition which may minimize the error.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.211-213
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• 2019

This paper proposes an image detection method, which can detect images regardless of the location and the direction of an image, required for automatic inspection based on machine vision technologies. A cable harness is considered in this paper as an inspection object, and implementation results of a technology of being applicable to a real cable harness production process is presented.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.55-56
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• 2020

The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.109-116
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• 2007

This study has reviewed the applicability of displacement measurement by using a digital vision technique based on typical photogrammetric methods. In this study, a series of experimental measurements have been performed in order to improve the accuracy of digital vision measurement by establishing criteria of factors of various vision measurements. It is found that the digital vision measurement tends to show higher accuracy as the image size(resolution) and the focal length become larger and the distance to an object becomes closer. It is also observed that measurement error decreases with processing as many images as possible in various angles. Applicability on high-resolution displacement measurement is proved by applying the digital vision measurement developed in this study to a large scale loading test of concrete lining.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.22-27
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• 2009

In this paper, an automatic functional inspection system EVT (Emulated Vision Tester) for LCD drive module PCB has been proposed and implemented. Typical automatic inspection system such as probing methods and vision-based systems are widely known and used, however, there exist undetectable defects due to critical timing factors which they may miss to catch from LCD equipments. Especially typical vision-based systems have inconsistency on acquisition of images so that distinction between gray scales can be difficult which results in low level of performance and reliability on the inspection results. The proposed EVT system is pure hardware solution. It directly compares pattern signals from a pattern generator to output signals from LCD drive module. It also inspects variety of analog signals such as voltage, resistance, wave forms and so forth. The EVT system not only shows high performance in terms of reliability and processing speed but reduces costs on inspection and maintenance. Also, full automation of entire production line can be realized when EVT is applied in in-line inspection processes.

• Design & Manufacturing
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• v.16 no.4
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• pp.60-66
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• 2022

Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.610-615
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• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.98-106
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• 2024

Due to advancements in construction technology and analytical tools, an increasing number of cable-stayed bridges have been designed and constructed in recent years. A cable is a structural element that primarily transmits the main load of a cable-stayed bridge and plays the most crucial role in reflecting the overall condition of the entire bridge system. In this study, a vision-based method was applied to estimate the tension of the stay cables located at a long distance. To measure the response of a cable using a vision-based method, it is necessary to install feature points or targets on the cable. However, depending on the location of the point to be measured, there may be no feature points in the cable, and there may also be limitations in installing the target on the cable. Hence, it is necessary to find a way to measure cable response that overcomes the limitations of existing vision-based methods. This study proposes a method for measuring cable responses by utilizing the characteristics of cable shape. The proposed method involved extracting the cable shape from the acquired image and determining the center of the extracted cable shape to measure the cable response. The extracted natural frequencies of the vibration mode were obtained using the measured responses, and the tension was estimated by applying them to the vibration method. To verify the reliability of the vision-based method, cable images were obtained from the Hwatae Bridge in service under ambient vibration conditions. The reliability of the method proposed in this study was confirmed by applying it to the vibration method using a vision-based approach, resulting in estimated tensions with an error of less than 1% compared to tensions estimated using an accelerometer.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.3-10
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• 2003

Developments in science and technology based on computer technology influenced military fields and created up-to-date weapons and equipment, and as a result, which is changing the war accomplishing methods of the future warfare. Due to these changes in the war accomplishing methods, the army command centers are requested to make changes in their decision-making process. In other words, they need to apply more scientific methods rather than just build a scheme by the mere analysis of commanders and the staffs as in the past. Consequently, we propose a model, Vision 21 we developed as a war game model for division-size unit analysis use, in the COA development process, which is the most important part in establishing the OPLAN for mission accomplishment. Vision 21, with a comparative analysis of the other COA built in the COA development process, can be applied to making the best COA. Model employment concept can let us choose the best COA, operating war games on condition that the COA of the opposite forces is fixed and ours sequentially opposed against, and with a comparative analysis also. Moreover, if the time available is limited, before establishing several courses, we can apply the COA to the process for making the best decision, analysing in stages or by main phases and not establishing several courses for a special purpose.