• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.111-121
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• 2011

This paper discusses a method for optimizing the semi-actuated traffic signal control system by adjusting the initial interval according to the number of vehicles waiting for the green light in the actuated phase. We also present a Left-Turn actuated traffic signal control strategy that examines the vehicular noise in the detection area and determines the phase extension and the gap-out. In order to detect the vehicles in real-time, an image detector's Video Image Tracking technology was adopted. A 'Zone in Zone'method was implemented, and the image detection area is segmented into three zones: 1) Zone1 for verifying a vehicles obligatory presence, 2) Zone2 for counting the standby vehicles, and 3) Zone3 for examining the number of vehicles that have passed. The on-site assessment of the Left Turn Actuated Control is carried out using CORSIM, and the results show that the Control Delay decreased by 23.10%, 15.06%, and 4.34% compared to the delays resulted from pre-timed control, semi-actuated control-1 and semi-actuated control-2 traffic signal control systems respectively. The Queue Time also decreased by 36.24%, 20.10% and the Total Time by 14.36%, 7.02% for the same scenario. Which clearly demonstrates the operational efficiency. A sensitivity analysis reveals that the improvement from the propose traffic control strategy tends to increase as the through traffic volume reaches a saturated condition and the left-turn traffic volume decreases.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1045-1059
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• 2011

A 3-D multi-function radar(MFR) is a modern radar to provide various target information, such as range, doppler, and angle by performing surveillance, multiple target tracking, and missile guidance. In this paper, we introduced a real-time radar signal processor(RSP), which is a crucial component of MFR with its design, implementation using high-speed multiple DSP, and performance. Additionally, we verified that several advanced signal processing algorithms were well-performed in our RSP, such as MCA-CFAR algorithm for target detection in clutter environment, range and velocity measurement algorithm using discriminator estimation, and noise jammer detection algorithm using local minimum selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.407-416
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• 2006

It is difficult for the movement detection of an object through a camera to detect exact movement because of unnecessary noises and changes of the light. It can be recognized as a background, when there is no movement after the inflow of an object. Therefore, It is necessary to fast search algorithm for tracking and extract of object that is realtime image. In this thesis, we evaluate the difference of the input vision based on initial image and replace some pixels in process of time. When there is a big difference between background image and input image, we decide it is the point of the time of the object input and then extract boundary point of it. The extracted boundary point detects precise movement of the object by creating minimum block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the performance test.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.64-76
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• 2008

To increase road safety at blackspots, it is needed to develop a new method that can process before accident occurrence. Accident situation could result from traffic conflict. Traffic conflict decision technique has an advantage that can acquire and analyze data in time and confined space that is less through investigation. Therefore, traffic conflict technique is highly expected to be used in many application of road safety. This study developed traffic conflict decision program that can analyze and process from signalized intersection image. Program consists of the following functional modules: an image input module that acquires images from the CCTV camera, a Save-to-Buffer module which stores the entered images by differentiating them into background images, current images, difference images, segmentation images, and a conflict detection module which displays the processed results. The program was developed using LabVIEW 8.5 (a graphic language) and the VISION module library.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.419-428
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• 2021

Shadow removal plays a key role for the pre-processing of image processing techniques such as object tracking and detection. With the advances of image recognition based on deep convolution neural networks, researches for shadow removal have been actively conducted. In this paper, we propose a novel method for shadow removal, which utilizes self attention distillation to extract semantic features. The proposed method gradually refines results of shadow detection, which are extracted from each layer of the proposed network, via top-down distillation. Specifically, the training procedure can be efficiently performed by learning the contextual information for shadow removal without shadow masks. Experimental results on various datasets show the effectiveness of the proposed method for shadow removal under real world environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.105-115
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• 2019

Recently, intelligent Android malicious codes have become difficult to detect malicious behavior by static analysis alone. Malicious code with SO file, dynamic loading, and string obfuscation are difficult to extract information about original code even with various tools for static analysis. There are many dynamic analysis methods to solve this problem, but dynamic analysis requires rooting or emulator environment. However, in the case of dynamic analysis, malicious code performs the rooting and the emulator detection to bypass the analysis environment. To solve this problem, this paper investigates a variety of root detection schemes and builds an environment for bypassing the rooting detection in real devices. In addition, SDK code hooking module for Android malicious code analysis is designed using Xposed, and intent tracking for code flow, dynamic loading file information, and various API information extraction are implemented. This work will contribute to the analysis of obfuscated information and behavior of Android Malware.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.975-985
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• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.81-90
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• 2005

In this paper, we propose a novel approach which models multilingual story link detection by adapting the features such as timelines and multilingual spaces as weighting components to give distinctive weights to terms related to events. On timelines term significance is calculated by comparing term distribution of the documents on that day with that on the total document collection reported, and used to represent the document vectors on that day. Since two languages can provide more information than one language, term significance is measured on each language space and used to refer the other language space as a bridge on multilingual spaces. Evaluating the method on Korean and Japanese news articles, our method achieved $14.3{\%}\;and\;16.7{\%}$ improvement for mono- and multi-lingual story pairs, and for multilingual story pairs, respectively. By measuring the space density, the proposed weighting components are verified with a high density of the intra-event stories and a low density of the inter-events stories. This result indicates that the proposed method is helpful for multilingual story link detection.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.465-472
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• 2005

In this paper, we propose the method of manipulating the gaze direction of 3D FPS game's character by using eye gaze detection from the successive images captured by USB camera, which is attached beneath HMB. The proposed method is composed of 3 parts. At first, we detect user's pupil center by real-time image processing algorithm from the successive input images. In the second part of calibration, when the user gaze on the monitor plane, the geometric relationship between the gazing position of monitor and the detected position of pupil center is determined. In the last part, the final gaze position on the HMD monitor is tracked and the 3D view in game is controlled by the gaze position based on the calibration information. Experimental results show that our method can be used for the handicapped game player who cannot use his(or her) hand. Also, it can Increase the interest and the immersion by synchronizing the gaze direction of game player and the view direction of game character.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2094-2105
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• 1994

This paper contains a Hough transform based projection method derived from Radon transform for tracking dim unresolved(sub-pixel) moving targets that move along straight line parths across a time sequential image data. In contrast to several recently presented Hough transform methods using a compressed image referred to as the track map our proposed technique utilizing a set of projections taken along arbitrary orientations effectively increases the changes of target detection, and creates a robust track estimation environment by incorporating all the available knowledge obtained from the projections. Moreover, in order to quantitatively assess the estimation capability of the projection-based Hough transform algorithm, the analytical bounds on the Hough space parameter errors introduced by image space noise contamination are derived. The simulation yielded promising results of estimating the track parameters even under low signal to noise rations when our technique was tested against the time sequential sets of real infrared image data referred to as the HiCamps.