• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.84-91
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• 2011

Recently, WBAN(Wireless Body Area Network) which has progressed standardization based on IEEE 802.15.6 standardization is a network for the purpose of the short-range wireless communications within around 3 meters from the inner or outer human body. Effective QoS control technique and data efficient management in limited bandwidth such as audio and video are important elements in terms of users and loads in short-range wireless networks. In this paper, for high-speed WBAN IEEE 802.15.6 standard, the dynamic allocation to give an efficient bandwidth management and weighted fair queueing algorithm have been proposed through the adjustment of the super-frame about limited data and Quality of Service (QoS) based on the queuing algorithm. Weighted Fair Queueing(WFQ) Algorithm represents the robust performance about elements to qualitative aspects as well as maintaining fairness and maximization of system performance. The performance results show that the dynamic allocation expanded transmission bandwidth five times and the weighted fair queueing increased maximum 24.3 % throughput and also resolved delay bound problem.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.353-361
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• 2020

Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3220-3226
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• 2011

In order to monitor internal risk factors such as fire, terror, etc. on the subway station, the surveillance systems using CCTV and various kinds of sensors have been implemented and recently, introduction of surveillance systems using an advanced IT technology, sensor network technology is tried on several areas. Since 2007, Korean government has made an effort to develop the intelligent surveillance and monitoring system, which can monitor fire, intrusion, passenger congestion, health-state of structure, etc., by using wireless sensor network technology and intelligent video analytic technique. For that purpose, this study carried out field wireless communication environment test on Chungmuro Station of Seoul Metro on the basis of ZigBee that is considered as a representative wireless sensor network before field application of the intelligent integrated surveillance system being developed, arranged and analyzed and ZigBee based wireless communication environment test results on the platform and waiting room of Chungmuro Station on this paper. Results of wireless spectrum analysis on the platform and waiting room showed that there is no radio frequency overlapped with that of ZigBee based sensor network and no frequency interference with adjacent frequencies separated 10MHz or more. As results of wireless data transmission test using ZigBee showed that data transmission is influenced by multi-path fading effect from the number and flow rate of passengers on the platform or the waiting room rather than effects from entrance and exit of the train to/from the platform, it should be considered when implementing the intelligent integrated surveillance system on the station.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.127-134
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• 2022

Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.17-26
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• 2016

This work proposes a 12b 60MS/s 0.18um CMOS Flash-SAR ADC for various systems such as wireless communications and portable video processing systems. The proposed Flash-SAR ADC alleviates the weakness of a conventional SAR ADC that the operation speed proportionally increases with a resolution by deciding upper 4bits first with a high-speed flash ADC before deciding lower 9bits with a low-power SAR ADC. The proposed ADC removes a sampling-time mismatch by using the C-R DAC in the SAR ADC as the combined sampling network instead of a T/H circuit which restricts a high speed operation. An interpolation technique implemented in the flash ADC halves the required number of pre-amplifiers, while a switched-bias power reduction scheme minimizes the power consumption of the flash ADC during the SAR operation. The TSPC based D-flip flop in the SAR logic for high-speed operation reduces the propagation delay by 55% and the required number of transistors by half compared to the conventional static D-flip flop. The prototype ADC in a 0.18um CMOS demonstrates a measured DNL and INL within 1.33LSB and 1.90LSB, with a maximum SNDR and SFDR of 58.27dB and 69.29dB at 60MS/s, respectively. The ADC occupies an active die area of $0.54mm^2$ and consumes 5.4mW at a 1.8V supply.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.557-562
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• 2020

In the non-face-to-face learning environment forced into effect by the COVID-19 pandemic, online learning is being adopted as a major educational technique. Given the lack of research on how online learning patterns affect academic performance, this study focuses on the number and duration of online video learning sessions as a major factor based on midterm and final exams, and with a formative assessment for each type of learning. The correlation of the learning effects was analyzed. The analysis focused on computer programming subjects, which are among the most difficult liberal arts subjects for arts and science students at the university level. The analysis of cases of actual students showed no correlation among weekly formative assessments, the number of learning sessions, and the learning duration. On the other hand, the number of learning sessions (r=.39 p<0.05) and learning duration (r=.42 p<0.05) were correlated with the midterm and final exams. Elements, such as SMS text, bulletin board, and e-mail, were excluded from the analysis because not all students have access to them. Therefore, the results can be improved if future analysis of the students' learning patterns in a non-face-to-face lecture environment is performed considering more factors/elements and the learners' needs.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.471-482
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• 2006

In this paper, we propose a new scheme to generate multi-view images utilizing depth map decomposition and adaptive edge smoothing. After carrying out smooth filtering based on an adaptive window size to regions of edges in the depth map, we decompose the smoothed depth map into four types of images: regular mesh, object boundary, feature point, and number-of-layer images. Then, we generate 3-D scenes from the decomposed images using a 3-D mesh triangulation technique. Finally, we extract multi-view images from the reconstructed 3-D scenes by changing the position of a virtual camera in the 3-D space. Experimental results show that our scheme generates multi-view images successfully by minimizing a rubber-sheet problem using edge smoothing, and renders consecutive 3-D scenes in real time through information decomposition of depth maps. In addition, the proposed scheme can be used for 3-D applications that need the depth information, such as depth keying, since we can preserve the depth data unlike the previous unsymmetric filtering method.