• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.59-67
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• 2002

Recently, much demand of vector data have increased rapidly such as a digital map instead of traditional a paper map and the raster data such as a high-resolution orthoimage have been used for many GIS application with the advent of industrial high-resolution satellites and development of aerial optical sensor technologies. Aerial photogrammetric technologies using an airship can offer cost-effective and high-resolution color images as well as real time images, different from conventional remote sensing measurements. Also, it can acquire images easily and its processing procedure is short and simple relatively. On the other hand, it has often been used for the production of a small-scale land use map not required high accuracy, monitoring of linear infrastructure features through mosaicking strip images and construction of GIS data. Through this study, the developed aerial photogrammetric system using the airship expects to be applied to not only producing of scale 1:5, 000 digital map but also verifying, editing, and updating the digital map which was need to be reproduced. Further more, providing the various type of video-images, it expects to use many other GIS applications such as facilities management, scenery management and construction of GIS data for Urban area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.791-799
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• 2008

An image recognition for surrounding conditions is very important in image transmission. In recently rears, as the information infrastructure is more general, the user-centered demands in which they want to identify by object's states image using wire or wireless environment have increased. However, existing mobile solution could be hard to expect high quality mage, because limitation of software processing according as network based on mobile terminal which has low band width supports software codec. To solve this weak point, this paper describes on hardware codec design based on MPEG-4 which is international video compression standard. Implemented system contains the embedded CPU for optimized design and it works high quality service as transmission speed and resolution in mobile circumstance.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• The Journal of Bigdata
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• v.3 no.2
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• pp.113-121
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• 2018

In this study, an augmented reality(AR)-based information management system for agricultural facility is proposed. Using a variety of sensed data transmitted by Lora-based wireless networks deployed at the agricultural facility, this system is capable of augmenting the sensed data and displaying them on the user's smartphone screen to provide visualized information to user. When users point their smartphone camera to the agricultural facility, the environment information collected from numerous sensors installed at the facility would be visualized and appear on the screen. Unlike traditional system which requires user to search a specific facility and then select sensor(s) to obtain the environment information, the proposed system shows the information on smartphone screen by augmenting it with real image captured by camera without doing a series of time-taking selection process. Since the way of acquiring information is through image or video, this system contributes to convenient monitoring and efficient management for agricultural facility.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.1-8
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• 2022

In Korea, drones, which are at the core of the 4th industrial revolution, are used to promote Korean New Deal policies to digitalize the SOC. Overseas, the use of convergence sensors, such as thermal imaging cameras, on drones is increasing in various industrial fields. In this research, to improve pavement quality in highway bridge pavement construction, a thermal imaging camera was mounted on a drone to measure and verify the temperature of the pavement work section. Using a laser thermometer allows the partial measurement of pavement temperature. It was confirmed that the proposed method allows not only real-time temperature monitoring of the whole pavement work section but also uniformity verification by checking temperature distribution. The proposed method has the potential to control highway pavement quality and enable quick decision-making on traffic opening times by reducing the possibility of misjudging road opening times(pavement surface temperature ≦ 40℃).

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.691-700
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• 2003

Due to the fast development of wire&wireless internet and computer hardware, more and more internet services are being developed, such as Internet broadcast, VoD (Video On Demand), etc. So QoS (Qualify of Service) is essentially needed to guarantee the quality of these services. Traditional Internet is Best-Effort service in which all packets are transported in FIFO (First In First Out) style. However, FIFO is not suitable to guarantee the quality of some services, so more research in QoS router and QoS protocol are needed. Researched QoS router and protocol are high cost and inefficient because the existing infra is not used. To solve this problem, a new QoS control method, named Network Adaptive QoS, is introduced and applied to client/server-based streaming systems. Based on network bandwidth monitoring mechanism, network adaptive QoS control method can be used in wire&wireless networks to support QoS in real-time streaming system. In order to reduce application cost, the existing streaming service is used in NAQoS. A new module is integrated into the existing server and client. So the router and network line are not changed. By simulation in heavy traffic network conditions, we proved that stream cannot be seamless without network adaptive QoS method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.156-163
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• 2015

In this paper, we propose an active water level and distance measurement algorithm using a light beam pattern. On behalf of conventional water level gauge types of pressure, float-well, ultrasonic, radar, and others, recently, extensive research for video analysis based water level measurement methods is gradually increasing as an importance of accurate measurement, monitoring convenience, and much more has been emphasized. By turning a reference light beam pattern on bridge or embankment actively, we suggest a new approach that analyzes and processes the projected light beam pattern image obtained from camera device, measures automatically water level and distance between a camera and a bridge or a levee. As contrasted with conventional methods that passively have to analyze captured video information for recognition of a watermark attached on a bridge or specific marker, we actively use the reference light beam pattern suited to the installed bridge environment. So, our method offers a robust water level measurement. The reasons are as follows. At first, our algorithm is effective against unfavorable visual field, pollution or damage of watermark, and so on, and in the next, this is possible to monitor in real-time the portable-based local situation by day and night. Furthermore, our method is not need additional floodlight. Tests are simulated under indoor environment conditions from distance measurement over 0.4-1.4m and height measurement over 13.5-32.5cm.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.