• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.2
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• pp.271-280
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• 2011

This paper presents a navigation system based on the tactical communication and vision system in outdoor environments which is applied to unmanned robot for perimeter surveillance operations. GPS errors of robot are compensated by the reference station of C2(command and control) vehicle and WiBro(Wireless Broadband) is used for the communication between two systems. In the outdoor environments, GPS signals can be easily blocked due to trees and buildings. In this environments, however, vision system is very efficient because there are many features. With the feature MAP around the operation environments, the robot can estimate the position by the image matching and pose estimation. In the navigation system, thus, operation modes is switched by navigation manager according to some environment conditions. The experimental results show that the unmanned robot can estimate the position very accurately in outdoor environment.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.953-954
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• 2008

Wireless Sensor Network (WSN) surveillance applications usually employed magnetometer for recognizing the ferrous objects. Novel magnetic sensing model which includes azimuth parameter is suggested to understand the anisotropic characteristic of magnetic field through numerous outdoor experiments.

• Journal of the Korean housing association
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• v.26 no.4
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• pp.95-104
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• 2015

Public rental housing in Korea has been initially provided for residential stability of low-income household focusing on solving quantitative insufficiency since 1980s. In the process of early stage of designing and planning public rental housing, qualitative aspects of considering children were not primary concern. This study aims to analyze the priority of environmental improvement of outdoor spaces for children's safety in public rental housing. First, literature review was performed in the reference of local residential safety guidelines, Universal Design, and CPTED guidelines. In each guidelines, common safety planning factors for children were extracted within different types of outdoor spaces. Second, based on literature analysis, residents evaluated importance and satisfaction level by different safety types, outdoor space type, and environmental planning factors. In results, residents evaluated high importance and showed low satisfaction for crime and traffic safety. Through IPA, facilities and parking space was evaluated where improvement is needed for the first priority, and planning factors were mostly concerned with surveillance and safety management system. Result shows general concern of public rental housing residents, about weak facility management and security system, and about socially isolated environment which heightened the fear of crime safety. Overall, poor maintenance of the complex environment and decrepit facilities are constantly raising risk of safety accidents especially for children. Considering residents' concern, environmental improvement should be considered in perspective of not only physical repair, but also facility management and security system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.12
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• pp.54-61
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• 2011

We propose a surveillance-alert system based on optimal placements of PDR(Pulsed Doppler Radar) sensors in USN. By using the detection information of moving target from PDR sensor and by considering the covered detection region and geographical property of the strategic area, three optimal placements of sensors are proposed. The proposed placement are named as the grid type, the linear type and the zigzag type. Also, the surveillance alert system based on three sensor placements are developed. The alert level of the proposed surveillance-alert system are 'Perception', 'Caution', 'Warning' and 'Danger' which are decided by the distance change between the moving targets and the command post. The performace of the developed system is verified via outdoor experiments.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.810-813
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• 2004

In this paper, a background initialization for video surveillance proposed. The proposed algorithm is that the background images are sampled n frames during ${\Delta}t$ All Sampling frames are divided by $M{\times}N$ size block every frame. Average values of pixels for same location block of the sampling frames during ${\Delta}t$t are taken. then the maximum intensity $\alpha$ and the minimun intensity $\beta$ is obtained, respecticely. The intial by $M{\times}N$ size block, then average intensity $\eta$ of pixels for the block is obtained. If the average intensity $\eta$ is out of the initial range of the background image, it is decided the moving object image, and if the average intensity $\eta$ is included in the initial range of the background image. it is decided the background image. To examine the propriety of the proposed algorithm in this paper, the accuracy and robustness evaluation results for human and car in the indoor and outdoor enviroment. the error rate of the proposed method is less than the existing methods and the extraction rate of the proposed method is better than the existing methods.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.10-21
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• 2016

Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.860-868
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• 2008

Human detection techniques in outdoor scenes have been studied for a long time to watch suspicious movements or to keep someone from danger. However there are few methods of human detection in overhead or near-field view scenes, while lots of human detection methods in far-field view scenes have been developed. In this paper, a set of five features useful for human detection in overhead view scenes and another set of four useful features in near-field view scenes are suggested. Eight feature-candidates are first extracted by analyzing geometrically varying characteristics of moving objects in samples of video sequences. Then highly contributed features for each view scene to classifying human from other moving objects are selected among them by using a neural network learning technique. Through experiments with hundreds of moving objects, we found that each set of features is very useful for human detection and classification accuracy for overhead view and near-field view scenes was over 90%. The suggested sets of features can be used effectively in a PTZ camera based surveillance system where both the overhead and near-field view scenes appear.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.160-168
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• 2019

In this study, we propose a verification method for a planar-phased array radar system using a near-field beam focusing(NFBF) test method. We then confirmed the validity of the results. The proposed method can be used to verify a radar system in the near-field range of twice the antenna aperture size, and this is done in the same manner as the field system performance test conducted in a non-outdoor electromagnetic anechoic chamber. The test configuration and procedure for verifying the NFBF using near-field energies were reviewed. In addition, the phase compensation values of additional individual channels were quantified through mathematical verification of the beam-steered NFBF test. Based on a theoretical verification, the actual NFBF test was performed and the validity of the test method was confirmed through comparison with ideal analytical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3104-3120
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• 2017

The intelligent monitoring system has been successfully applied in many fields such as: monitoring of production lines, transportation, etc. Smart surveillance systems have been developed and proven effective in some specific areas such as monitoring of human activity, traffic, etc. Most of critical application monitoring systems involve object tracking as one of the key steps. However, task of tracking of moving object is not easy. In this paper, the authors propose a method to implement human object tracking in outdoor environment based on human features in shearlet domain. The proposed method uses shearlet transform which combines the human features with context-sensitiveness in order to improve the accuracy of human tracking. The proposed algorithm not only improves the edge accuracy, but also reduces wrong positions of the object between the frames. The authors validated the proposed method by calculating Euclidean distance and Mahalanobis distance values between centre of actual object and centre of tracked object, and it has been found that the proposed method gives better result than the other recent available methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1647-1654
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• 2013

Detection performance of the vehicle on the road depends on weather conditions, the shadow by the movement of the sun, or illumination changes, etc. In this paper, a vehicle detection system in conjunction with a robust background estimate algorithm to environment change on the road in daytime is proposed. Gaussian Mixture Model is applied as background estimation algorithm, and also, Adaboost algorithm is applied to detect the vehicle for candidate region. Through the experiments with input videos obtained from a various weather conditions at the same actual road, the proposed algorithm were useful to detect vehicles in the road.