• Korean Security Journal
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• no.31
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• pp.187-207
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• 2012

The purpose of this study was to analyze the punching movement at the horseback riding stance, one of the basic movements in Taekwondo, with 3D images and further the kinetic variables such as time, velocity, angle, angular velocity, and angular acceleration according to the types. It also aimed to examine the characteristics of each type and suggest instructional methods for the right punching movement. For those purposes, three members from the College Taekwondo Poomse Demonstration Squad were put to the test. The research findings led to the following conclusions: 1. Performance Time of the Punching Movement : In Section 1, Type 1 and 2 recorded $0.24{\pm}0.07s$ and $0.42{\pm}0.08s$, respectively, for the punching movement at the horseback riding stance. While Type 1 took less performance time in the punching movement, Type 2 took less time for take back according to each section's percentage in the total performance time. 2. Variables of Linear Velocity and Linear Acceleration : Each type recorded different linear velocity for each aspect, but the highest linear velocity represented the moment of impact for each type. Type 2 recorded the highest linear velocity in Aspect 4, which was the moment of impact. 3. Variable of Joint Angle : There were no big outer differences in the joint angle during the punching movement between Type 1 in the aspect of impact and Type 2, but the individuals assumed dynamic positions in the punching movement of Type 2 with more diverse changes to the joint angle. 4. Variables of Angular Velocity and Angular Acceleration During the punching movement of Type 1, the Aspect 3 in the moment of impact recorded angular velocity of $0.79{\pm}0.02deg/s$, $0.91{\pm}0.04deg/s$, and $5.24{\pm}0.09deg/s$ at the pelvis, shoulder, and wrist respectively. During the punching movement of Type 2, the Aspect 3 in the moment of impact recorded angular velocity of $1.32{\pm}0.03deg/s$, $0.21{\pm}0.03deg/s$, and $4.98{\pm}0.08deg/$ at the shoulder, wrist, and pelvis, respectively. In the Aspect 3 in the moment of impact in Type 2, the angular acceleration at the right wrist joint was $176.24{\pm}1.11deg/s^2$, which was bigger than that in the moment of impact in Type 1.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.664-672
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• 2004

Widespread popularity of wireless data communication devices, coupled with the availability of higher bandwidths, has led to an increased user demand for content-rich media such as images and videos. Since such content often tends to be private, sensitive, or paid for, there exists a requirement for securing such communication. However, solutions that rely only on traditional compute-intensive security mechanisms are unsuitable for resource-constrained wireless and embedded devices. In this paper, we propose a selective partial image encryption scheme for image data hiding , which enables highly efficient secure communication of image data to and from resource constrained wireless devices. The encryption scheme is invoked during the image compression process, with the encryption being performed between the quantizer and the entropy coder stages. Three data selection schemes are proposed： subband selection, data bit selection and random selection. We show that these schemes make secure communication of images feasible for constrained embed-ded devices. In addition we demonstrate how these schemes can be dynamically configured to trade-off the amount of ded devices. In addition we demonstrate how these schemes can be dynamically configured to trade-off the amount of data hiding achieved with the computation requirements imposed on the wireless devices. Experiments conducted on over 500 test images reveal that, by using our techniques, the fraction of data to be encrypted with our scheme varies between 0.0244％ and 0.39％ of the original image size. The peak signal to noise ratios (PSNR) of the encrypted image were observed to vary between about 9.5㏈ to 7.5㏈. In addition, visual test indicate that our schemes are capable of providing a high degree of data hiding with much lower computational costs.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4814-4821
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• 2012

An e-passport is equipped with bio information by adding the non-attachable IC chip with a smart function. In order to solve such a problem, the user's privacy is protected by using the BAC, PA, AA and EAC mechanisms. However, the password key used in the BAC mechanism is made of the combination of the MRZ values. As a result, it is possible to decode the password by using the indiscriminate attacking program after finding out the combined rules of MRZ. This thesis suggests the mechanism with an improved level of efficiency through the time-stamp values by using the information of images and fingerprints and checking the forge or falsification of the e-passport when establishing a safe channel between the chip of the e-passport and the decoding system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.84-90
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• 2020

As the uploading and downloading of data through the Internet is becoming more common, data including personal information are easily exposed to unauthorized users. In this study, we detect a target area in images that contain personal information, except for the background, and we protect the detected target area by using a blocking method suitable for the surrounding situation. In this method, only the target area from color image input containing personal information is segmented based on skin color. Subsequently, blurring of the corresponding area is performed in multiple stages based on the surrounding situation to effectively block the detected area, thereby protecting the personal information from being exposed. Experimental results show that the proposed method blocks the object region containing personal information 2.3% more accurately than an existing method. The proposed method is expected to be utilized in fields related to image processing, such as video security, target surveillance, and object covering.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.27-32
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• 2020

High-resolution images taken by drones are being used for a variety of information, including monitoring. The management of agricultural facilities still uses mostly human survey methods. Surveying agricultural facilities, surveying the appearance of agricultural facilities, and the sleeping environment have legal and environmental constraints that are inaccessible to humans. In addition, in an area where information such as 3D maps and satellite maps are outdated or not provided, human investigation is inevitable, and a lot of time and money are invested. The purpose of this research is to design and develop drone system for field support incorporating AR smart glasses technology for the maintenance and management of agricultural facilities to improve the difficulties of using existing drones. In addition, We will also suggest ways to secure the safety of personal information in order to solve the damages caused by the exposure of personal information that may occur through video shooting.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.39-45
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• 2020

Recently the terrors have been attempted in the public places of the nations such as United states, England and Japan by explosive things, toxic materials and so on. It is understood that the method in which dangerous objects are put in public places is one of the difficult types in detection. While there are the cameras recording videos for many spots in public places, it is very hard for the security personnel to monitor every videos. Nowadays the smart softwares which can analyzing videos automatically are utilized to detect abandoned objects. The method by Lin et al. shows comparatively high detection rates for abandoned objects but it is not easy to obtain the shape information because there is a tendency that the number of the pixels decreases abruptly along the time goes due to the characteristics of short-term background images. In this research a novel method is proposed to successfully extract the shape of the abandoned object by analysing the characteristics of area variation. The experiment results show that the proposed method has better performance in extracting shape information in comparison with the precedent approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.693-698
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• 2018

This paper proposes a vehicle detection method for parking areas using unmanned aerial vehicles (UAVs) and using YOLOv2, which is a recent, known, fast, object-detection real-time algorithm. The YOLOv2 convolutional network algorithm can calculate the probability of each class in an entire image with a one-pass evaluation, and can also predict the location of bounding boxes. It has the advantage of very fast, easy, and optimized-at-detection performance, because the object detection process has a single network. The sliding windows methods and region-based convolutional neural network series detection algorithms use a lot of region proposals and take too much calculation time for each class. So these algorithms have a disadvantage in real-time applications. This research uses the YOLOv2 algorithm to overcome the disadvantage that previous algorithms have in real-time processing problems. Using Darknet, OpenCV, and the Compute Unified Device Architecture as open sources for object detection. a deep learning server is used for the learning and detecting process with each car. In the experiment results, the algorithm could detect cars in a dense area using UAVs, and reduced overhead for object detection. It could be applied in real time.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1059-1067
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• 2011

Next-Generation ITS environment requires high-speed data packet transmission, security, authentication, and hand-over supportable for driving vehicle on road by installing RSEs and OBUs. Therefore, wireless communication technology for next-generation ITS services are advancing to 200km/h maximum speed supportable, 1km communication radius, minimum 10Mbps hish-speed datarate for multimedia data(such as text, images, movie clips and so on) supportable, high reliability. In this paper, we implemented WAVE communication system which based on IEEE 802.11p PHY/MAC and evaluated that the system meets next-generation ITS environments.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.17-25
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• 2014

In the devices that leave video records, it is an important issue to distinguish whether the input image is a real object or a photo when securing an identifying image. Using a single image and sensor, which is a simple way to distinguish the target from distance measurement has many weaknesses. Thus, this paper proposes a way to distinguish a simple photo and a real object by using stereo images. It is not only measures the distance to the target, but also checks a three-dimensional effect by making the depth map of the face area. They take pictures of the photos and the real faces, and the measured value of the depth map is applied to the learning algorithm. Exactly through iterative learning to distinguish between the real faces and the photos looked for patterns. The usefulness of the proposed algorithm was verified experimentally.