• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.9-21
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• 2017

The purpose of this study is to identify the current situation and actual condition of the video security industry, The research method was based on interviews with twelve specialists, and examined the market trends, the problems of the video security industry, the improvement plan and the government promotion strategy. The problem with the domestic video security industry is that there are the decline in overseas exports and the slowdown in exports to China, insufficient measures to overcome certification barriers due to the strengthening of national certification system, domestic demand growth slowed, expansion of domestic market share of Chinese products, lack of high-tech development of domestic products, lack of expertise in technology development and operation and inadequate legislation for revitalizing the video security industry. The improvement plan is as follows. Need to implement export expansion support policy, need to build tailored response system for each country, need improvement of security related demand creation system, take measures such as domestic industrial protection policy, certification barriers and tariff barriers, induce future core technology to create high added value. The government also needs to actively support human resources development, and induce stabilization of relevant laws and institutions. This study will contribute to the development of related industries by suggesting the development direction of the video security industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.420-420
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• 2011

도시지역의 내수침수피해는 거의 매년 발생하고 있으며, 반지하와 같은 거주공간이 매우 취약한 상태이다. 특히 최근에는 지하철, 지하상가 등이 대규모 개발되고 복합네트워크화 되어 지하공간의 침수대책과 대피방안 마련이 시급한 상황이다. 일본의 경우 2000년 토카이 호우피해 후 통합유출해석 모형을 개발하였으며, 1999년 및 2003년 후쿠오카 침수피해 발생 후 특정도시하천침수피해대책법을 제정, 1999 후쿠오카, 2004년 하마마츠, 2008년 카누마 피해 후 일본 방재연구소에서는 실시간 1차원 지표범람모형과 모니터링을 통한 실시간 내수침수지도를 개발하였다. 특히 지하공간에 대해서는 "지하공간에 유입하는 범람수가 계단상 보행자게에 주는 위험성에 관한 연구" 등 실험을 바탕으로 각종 지하공간 침수대책 매뉴얼 및 지하시설의 침수시 피난확보계획 지침, 지하공간 침수대책 가이드라인 등 인명피해를 줄이고자하는 노력이 계속되어 오고 있다. 우리나라는 2006년 경기도 고양시 3호선 정발산역이 침수되었으며, 2010년 서울시 지하철 2호선 사당역 및 4호선이 침수되는 등의 지하철 침수피해와 2010년 서울시 광화문 지하상가, 인천시 부평구 우림라이온스 벨리, 우남플라자, 계양구 농협하나로마트, 서원아파트 등의 지하상가와 지하다층의 침수피해가 발생하였다. 특히 2006년 3호선 정발산역 침수는 17시간이나 지하철이 불통되었고 이로 인하여 심각한 교통 체증이 유발 되었다. 본 연구에서는 2010년 집중호우로 인한 서울, 인천지역의 지하공간 침수피해를 중심으로 최근 10년간 지하공간 침수피해사례로부터 대표적인 침수피해 원인 및 특성을 정리하였으며, 그 결과 지하공간 침수의 주요원인은 지상공간의 침수류가 지하공간으로 유입하고, 지하공간의 배수설비 용량부족, 지하공간으로의 유입을 방지하기위한 방지턱, 차수판, 침수시 비상전원 공급, 침수시 지하공간 대피 매뉴얼의 부재 등 다양한 원인이 있는 것으로 나타났다. 특히, 소방방재청에서 고시한 '지하공간 침수방지를 위한 수방기준'에 지하공간 침수 방지를 위한 각종 시설의 설치 및 대피 경로지정 등에 대한 기준이 마련되어 있으나, 지하공간 중 유동인구가 가장 많은 지하철역에서 조차 침수에 대한 행동매뉴얼이나 대피에 대한 가이드라인이 마련되지 않은 것으로 나타났다. 따라서, 지하공간 침수를 방지하기 위하여 센서를 이용한 자동 차수판과 경보기 설치, 지하공간의 사람들이 안전한 대피로를 찾을 수 있도록 지상공간 및 지하공간 출입구를 모니터링 할 수 있는 CCTV의 설치, Dry Area를 두어 비상대피 할 수 있는 공간의 마련 등 시설적인 부분에 대하여 '지하공간 침수방지를 위한 수방기준'을 더욱 강화할 필요가 있으며, 지상공간의 침수 상황을 고려한 지하공간의 대피매뉴얼 또는 가이드라인 등의 수립이 필요하다. 또한 이와 더불어 재산 및 인명피해를 더욱 효율적으로 줄일 수 있도록 실시간 예 경보를 위한 침수해석 모형의 개발이 시급하다.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.3
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• pp.81-90
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• 2018

Due to the dramatic advancement of IoT (Internet of Things), it is expected that tens of billions of IoT devices will be connected by the year 2024. Furthermore, as IoT technologies evolves, the security management in IoT platforms has become a critical issue. For example, there are interworking problems between heterogeneous IoT platforms caused by differences from communication protocols, security policies, etc. in each platform. In addition, unsecured interworking can cause major security issues including the information leakage. In this paper, in order to solve these problems, a security interworking architecture is proposed and implemented in both FIWARE and oneM2M, which are representative IoT platforms. First, the security architecture of FIWARE is analyzed and implemented, and then the security framework based on OAuth 2.0 is developed on Mobius platform. Finally, in order to validate the proposed security interworking architecture, a LED (Light-Emitting Diode) example, where the LED is controlled by only authorized users, is developed. The proposed architecture can be extended to the diverse IoT platforms and devices.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.195-206
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• 2004

One of the main factors which reduces the efficiency of a sewage treatment plant is the Inflow/Infiltration(Ⅰ/Ⅰ) in the sewer First we must calculate the quantity of Ⅰ/Ⅰ via the investigation of each sewer to establish the reduction plan of Ⅰ/Ⅰ. However, in Korea, we apply the results of a surveyed sample to the entire study area to establish the reduction plan of Ⅰ/Ⅰ. This methodology just considers the total Ⅰ/Ⅰ for the entire study area but it does not consider the quantity of Ⅰ/Ⅰ for the individual sewer systems. Therefore, we may need the model to consider the Ⅰ/Ⅰ in the individual sewer systems and we develop the model to calculate the Ⅰ/Ⅰ that happen in urban sewer systems. We estimate the Ⅰ/Ⅰ of individual systems by the developed model and the estimated Ⅰ/Ⅰ are utilized as the basic data for the establishment of Ⅰ/Ⅰ reduction plan. The observed Ⅰ/Ⅰ for the entire study area is distributed into the individual sewer systems according to their defect states. Here, the weights of defect elements are calculated using AHP(Analytic Hierarchy Process) and we perform the uncertainty analysis for considering the errors using MCS(Monte Carlo Simulation).

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Journal of Korea Game Society
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• v.11 no.5
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• pp.67-78
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• 2011

This paper introduces an efficient and satisfactory search interface that enables users to browse and find the video data they want from a massively huge video database widely used in various multimedia environment. The target user group is information analysts at US defense industry or governmental intelligence agencies whose job is to identify a certain person from a lot of video footage taken from CCTV(Closed-circuit Television) cameras. For the first user test, we suggested the CAVE-like virtual reality interface to be the most optimal for the tasks we designed for, so we compared this interface with desktop interface. The softwares and database developed and optimized for each task were used in this user test. For the second user test, we researched on what input devices would be most optimal for enhancing efficiency of search task in the CAVE-like virtual reality system. Especially we focused our effort on measuring the effectiveness and user satisfaction of three different types of devices that embody gestural interface input system that encourages users' ergonomic control of the interface. We also measured the time consumed for performing each task to find out the most efficient input device among the ones tested.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.7-13
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• 2019

Unlike a typical video wall system, video wall systems used for integrated monitoring in smart city environments should be able to display various videos, images, and texts simultaneously. In this paper, we propose an Internet Protocol (IP)-based video wall system that has no limit on the number of videos that can be monitored simultaneously, and that can arrange the monitor screen layout without restrictions. The proposed system is composed of multiple display servers, a wall controller, and video source providers, and they communicate with each other through an IP network. Since the display server receives and decodes the video stream directly from the video source devices, and displays it on the attached monitor screens, more videos can be simultaneously displayed on the entire video wall. When one video is displayed over several screens attached to multiple display servers, only one display server receives the video stream and transmits it to the other display servers by using IP multicast communications, thereby reducing the network load and synchronizing the video frames. Experiments show that as the number of videos increases, a system consisting of more display servers shows better decoding and rendering performance, and there is no performance degradation, even if the display server continues to be expanded.