• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.157-164
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• 2010

Recently, the Radio Frequency Identification(RFID) system has been growing with many promising features in technology and applications fields. Especially, a lot of efforts for the application of RFID system in the field of logistics management have been conducted. In addition, in logistics section of steel industry a remarkable efficiency can be attained by application of the RFID system. However, in the RFID system applied for the steel industry, lots of problems were found to be solved in recognition of the tags and antennas. This paper presents the feasibility of deploying RFID in the steel industry as a tool for reduction of the production cost. An application of the steel industry to RFID-based tracking management system was proposed. The results of this paper showed that the recognition rate of material input and output was found 100 percent and secured 99 percent of detection rate in the location. In conclusion, the proposed RFID-based tracking management system was approved superior to the existing system in terms of productivity.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.1
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• pp.19-28
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• 2007

Tunnel management is a time-consuming and expensive task. In particular, visual analysis of tunnel inspection often requires extended time and cost and shows problems on data gathering, storage and analysis. This study proposes a new approach to extract information for tunnel management by using a laser scanning technology. A prototype tunnel laser scanner developed was used to obtain point clouds of a railway tunnel surface. Initial processing of laser scanning data was to separate those laser pulses returned from the installations attached to tunnel liner using radiometric and geometric characteristics of laser returns. Once the laser returns from the installations were separated and removed, physically damaged parts on tunnel lining are detected. Based on the plane formed by laser scanner data, damaged parts are detected by analysis of proximity. The algorithms presented in this study successfully detect the physically damaged parts which can be verified by the digital photography of the corresponding location on the tunnel surface.

• Progress in Medical Physics
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• v.27 no.3
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• pp.162-168
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• 2016

Proton therapy is increasingly being actively used in the treatment of cancer. In contrast to photons, protons have the potential advantage of delivering higher doses to the cancerous tissue and lower doses to the surrounding normal tissue. However, a range shifter is needed to degrade the beam energy in order to apply the pencil beam scanning technique to tumors located close to the minimum range. The secondary neutrons are produced in the beam path including within the patient's body as a result of nuclear interactions. Therefore, unintended side effects may possibly occur. The research related to the secondary neutrons generated during proton therapy has been presented in a variety of studies worldwide, since 2007. In this study, we measured the magnitude of the secondary neutron dose depending on the location of the detector and the use of a range shifter at the beam nozzle of the proton scanning mode, which was recently installed. In addition, the production of secondary neutrons was measured and estimated as a function of the distance between the isocenter and detector. The neutron dose was measured using WENDI-II (Wide Energy Neutron Detection Instruments) and a Plastic Water phantom; a Zebra dosimeter and 4-cm-thick range shifter were also employed as a phantom. In conclusion, we need to consider the secondary neutron dose at proton scanning facilities to employ the range shifter reasonably and effectively.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1949-1954
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• 2016

Smart grid technology can be called grid techniques to improve the efficiency of the electric power by exchanging bidirectional information of electric power with real-time between electric power suppliers and consumers. Recently, the solar power generation system is being applied actively. However the solar power system has several problems leading to reduce overall electricity generation, because the difficult of the diagnosis and the solar power system failure such as PV(PhotoVoltaics) and inverter. In order to build an efficient smart grid, a stable electric power energy requirements capture and management and early fault detection is essentially required in solar power generation system. In this paper, it is designed to monitor the operating status of the solar power monitoring system from a remote location through a RS-485 or TCP/IP communication module to monitoring the output of solar power energy and abnormal phenomenon, to developing the measurement module and to transfer measured data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.120-128
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• 2017

The refraction phenomenon of radio waves should be considered to improve the detection accuracy of target altitudes for long-range surveillance radars, however, it is difficult to estimate accurate refractivity of atmosphere for every location. In this paper, we propose the atmosphere evaluation metric(AEM) to estimate atmospheric conditions at target locations using target altitudes obtained from primary surveillance radar(PSR) and secondary surveillance radar(SSR). To verify the suitability of the proposed metric, we observed atmospheric conditions and calculated estimation errors of target altitudes using measured data.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.213-218
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• 2021

In this paper, we detect and track vehicles by type based on highway daytime driving videos taken with black boxes for vehicles. In addition, we design a real-time MR contents production method that can be newly created by placing substitute videos of each type of detected vehicles in the same location as the new background video. To detect and track vehicles by type, we use the YOLO algorithm. And we also use the mask technique based on RGB color for substitute videos of each type of vehicles detected. The size of the vehicle substitute videos to be used for MR content are substituted by the same size as the area size of the detected vehicles. In this paper, we confirm that real-time MR contents design is possible as a result of experiments and simulations and believe that It will be usefully utilized in the field of VR contents.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.