• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.93-99
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• 2020

It seems to be increased rapidly that practical uses of intelligent Dron for public mission performance such as surveillance, prevention of disaster accident, relief etc with Dron technology development. Dron is needed for major technology realization of detection and trace technology of target, flight control and obstacle avoidance during flighting, detection and control of landing point functions to use smart safety-city platform construction. This dron system cause a great ripple effect technically and promote industrialization in the field of new technology. In this paper, an effective analysis and design method of dron system software will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.193-198
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• 2015

A large number of vision applications rely on matching keypoints across images. Pedestrian detection is under constant pressure to increase both its quality and speed. Such progress allows for new application. A higher speed enables its inclusion into large systems with extensive subsequent processing, and its deployment in computationally constrained scenarios. In this paper, we focus on improving the speed of pedestrian detection using HOG(histogram of oriented gradient) and multi frame operation which is robust to illumination changes in cluttering images. The result of our simulation indicates that the detection rate and speed of the proposed method is much faster than that of conventional HOG and differential images.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.13-20
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• 2024

This paper introduces a method for generating model images that can identify specific cylindrical medicine containers in videos and investigates data collection techniques. Previous research had separated object detection from specific object recognition, making it challenging to apply automated image stitching. A significant issue was that the coordinate-based object detection method included extraneous information from outside the object area during the image stitching process. To overcome these challenges, this study applies the newly released YOLOv8 (You Only Look Once) segmentation technique to vertically rotating pill bottles video and employs the ORB (Oriented FAST and Rotated BRIEF) feature matching algorithm to automate model image generation. The research findings demonstrate that applying segmentation techniques improves recognition accuracy when identifying specific pill bottles. The model images created with the feature matching algorithm could accurately identify the specific pill bottles.

• Smart Media Journal
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• v.11 no.11
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• pp.40-48
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• 2022

In this paper, an educational kit that can be used in AI education was developed to solve the difficulties of AI education. Through this, object detection and person detection in computer vision using CNN and OpenCV to learn practical-oriented experiences from theory-centered and user image recognition (Your Own) that learns and recognizes specific objects Image Recognition), user object classification (Segmentation) and segmentation (Classification Datasets), IoT hardware control that attacks the learned target, and Jetson Nano GPIO, an AI board, are developed and utilized to develop and utilize textbooks that help effective AI learning made it possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2043-2052
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• 1997

The object-oriented coding technique which is one of the coding methods in very low bit rate environment is suitable for videophone image sequence. The selection of source model affect image analysis. In this paper, an image analysis method for the object-oriented coding is presented. The process is composed of changed region detection andmotion estimateion. First, we use the standard deviation of frame difference as thrreshold to extract themoving area. If thesum of gray values in mask is greater than the threshold, the center pixel of the mask is regarded as moving region. After moving is detected in changed region by edge operator, observation point is determined from moving region. The motion is estimated by 6-parameter mapping method with determined observation point. The experimantal resutls show that the proposed method can significantly improve the image quality.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.363-364
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• 2008

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.96-102
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• 2002

Current testing(Iddq testing) on monitoring the quiescent power supply current is an efficient and effective method for CMOS bridging faults. The applicability of this technique, however, requires careful examination. Since cardinality of bridging fault is O($n^2$) and current testing requires much longer testing time than voltage testing, it is important to note that a bridging fault is untestable if the two bridged nodes have the same logic values at all times. Such faults should be identified by a good ATPG tool; otherwise, the fault coverage can become skewed. In this paper, we present an object-oriented redundant fault detection scheme for efficient current testing. Experimental results for ISCAS benchmark circuits show that the improved method is more effective than the previous ones.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1181-1190
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• 2013

The GOOSE(Generic Object Oriented Substation Event) is used as a network protocol to communicate between IEDs(Intelligent Electronic Devices) in international standard IEC 61850 of substation automation system. Nevertheless, the GOOSE protocol is facing many similar threats used in TCP/IP protocol due to ethernet-based operation. In this paper, we develop a IDS(Intrusion Detection System) for secure GOOSE Protocol using open software-based IDS Snort. In this IDS, two security functions for keyword search and DoS attack detection are implemented through improvement of decoding and preprocessing component modules. And we also implement the GOOSE IDS and verify its accuracy using GOOSE packet generation and communication experiment.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.3
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• pp.163-175
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• 1996

This paper invetigates estimation methods of mapping parameters in object-oriented coding. In this paper, we propose a fast parameter estimation method with its performance similar to that of the conventional methods. We employ hierarchical structure in difference images to redcue the computational complexity and also combine conventional six- and eight-mapping parameter estimation methods to compensate for the performance degradation caused by employment of hierarchical structure. Computer simulation shows that the proposed mehtod gives results similar to conventional methods with greatly reduced computational complexity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.682-691
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• 2017

In this paper, we propose the fusion design methodology of both pedestrian detection and object tracking system realized with the aid of HOG-PCA based RBFNN pattern classifier. The proposed system includes detection and tracking parts. In the detection part, HOG features are extracted from input images for pedestrian detection. Dimension reduction is also dealt with in order to improve detection performance as well as processing speed by using PCA which is known as a typical dimension reduction method. The reduced features can be used as the input of the FCM-based RBFNNs pattern classifier to carry out the pedestrian detection. FCM-based RBFNNs pattern classifier consists of condition, conclusion, and inference parts. FCM clustering algorithm is used as the activation function of hidden layer. In the conclusion part of network, polynomial functions such as constant, linear, quadratic and modified quadratic are regarded as connection weights and their coefficients of polynomial function are estimated by LSE-based learning. In the tracking part, object tracking algorithms such as mean shift(MS) and cam shift(CS) leads to trace one of the pedestrian candidates nominated in the detection part. Finally, INRIA person database is used in order to evaluate the performance of the pedestrian detection of the proposed system while MIT pedestrian video as well as indoor and outdoor videos obtained from IC&CI laboratory in Suwon University are exploited to evaluate the performance of tracking.