• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1563-1566
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• 2015

보안과 관련된 기술이 발전하여 대규모의 장소에 적합한 보안시스템들이 많이 개발되었다. 특히 CCTV를 이용한 감시카메라의 형태도 다양화되었다. 스마트폰의 어플리케이션이나 웹을 통해서 어디서든 감시할 수도 있어, 이를 통해 보안사고 시에 빠른 대처가 가능하다. 하지만 대규모 시스템이 아닌 경우에는 침입자 발견이 늦고, 뒤늦은 대처로 인해 큰 피해가 발생할 수 있다. 라즈베리파이, 실드 보드 등 기타 하드웨어들을 통하여 침입자를 스스로 감지하여 사용자에게 즉시 알림을 전송함으로써 보안사고에 대한 대처를 빠르고 효율적으로 할 수 있는 보안카메라를 구현하였다. 본 보안 시스템은 소리의 방향을 계산하고 정확한 방향으로의 보정을 통하여 최초 침입자를 인식한다. 이후 이미지트래킹을 통하여 침입자를 추적한다. 무선 네트워크를 이용하기 때문에 네트워크가 지원되는 어느 장소에서든지 사용이 가능하다. 대규모 보안시스템을 설치할 여건이 되기 어려운 작은 공장, 상가, 사무실 등에서 보안시스템으로 사용되면 유용할 것이다. 자세한 개발 내용은 본문에 기술한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.6-9
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• 2015

현대인들의 생활수준 향상과 기술의 발전에 따라 보안, 안전 등 미처 고려되지 않던 분야들이 다양한 영역에서 부각되면서 CCTV, IP카메라, 차량용 블랙박스와 같은 영상기반 시스템에 대한 시장수요가 증가하고 있다. 이에 맞춰 다양한 영상기반 시스템들이 개발되고, 개발 단계에서 낭비되는 시간을 줄이기 위해 프로토타이핑의 필요성이 대두되고 있지만 기존의 프로토타이핑을 위한 도구는 비용이나 속도측면에서 제한적이다. 본 논문에서는 영상기반 시스템 중 블랙박스의 하드웨어를 풀 시스템 에뮬레이터를 이용하여 모델링하고 수행되는 명령어 추출을 통해 시스템의 특성을 예측할 수 있는 하드웨어 프로토타이핑 도구를 제안한다. 또한 ARM 시스템용으로 컴파일 된 프로그램의 실행 여부를 확인하고, 프로그램을 구성하는 명령어와 추출도구를 통해 추출된 명령어를 비교하여 동작을 확인한다.

• Journal of IKEEE
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• v.25 no.1
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• pp.83-87
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• 2021

In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• Fire Science and Engineering
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• v.34 no.2
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• pp.86-93
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• 2020

This study aims to maintain the safety of an outdoor storage tank through the fundamental case analysis of explosion and fire accidents in the storage tank. We consider an accident caused by the explosion of fire inside the tank, as a result of the gradual spreading of the residual fire generated by wind lamps flying off a workplace in the storage tank yard. To determine the cause of the accident, atmospheric diffusion conditions were derived through CCTV image analysis, and the wind direction was analyzed using computational fluid dynamics. Additionally, the amount of oil vapor inside the tank when the floating roof was at the lowest position, and the behavior of the vapor inside the tank when the floating roof was at the highest position were investigated. If the cause of the explosion in the storage tank is identified and the level of the storage tank is maintained below the internal floating roof, dangerous liquid fills the storage tank, and the vapor in the space may stagnate on the internal floating roof. We intend to improve the operation procedure such that the level of the storage tank is not under the Pontoon support, as well as provide measures to prevent flames from entering the storage tank by installing a flame arrester in the open vent of the tank.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.59-59
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• 2003

목적 : 환자의 호흡에 의한 움직임 및 부정확한 환자 자세 setup 때문에 3 차원 전신 정위 방사선치료,3 차원 입체조형 방사선치료 IMRT와 같은 방사선 치료기술에서 병소에 대한 정확한 표적 위치측정은 매우 어려운 실정이다. 그러므로 본 연구는 방사선 치료시 환자의 움직임을 최대한 고정시켜 줄 수 있으며 환자 자세에 대한 setup 오차를 감소시키고 환자 전신에 산재한 병소의 위치를 좌표화할 수 있는 전신 정위 프레임 제작과 제작한 프레임에 대한 고정효과 및 재현성을 나타내는 환자 자세의 setup 오차를 평가하는데 있다. 재료 및 방법 : 자체 제작한 전신 정위 프레임 구조는 CT 영상 촬영 가능성에 중점을 두고 병소 표적의 좌표실현 및 환자체형에 따른 다양성 그리고 프레임에 대한 견고성 및 안정성 확인에 초점화하여 제작하였다. 이렇게 제작된 전신 정위 프레임에 대한 방사선 투과율 측정 실험과 CCTV 카메라와 DVR(Digital Video Recorder)를 이용해 환자 자세 변화에 대한 영상을 획득하여 matlab으로 구현한 오차분석용 프로그램으로 환자 외부자세에 대한 오차 비교 평가하고 CT 촬영에 의한 가상표적 위치측정 실험을 수행하였다. 또 한 고정벨트 추가 사용으로 인한 환자의 고정효과 정도를 살펴보았다. 결과 : 제작된 전신 정위 프레임에 대한 방사선 투과율은 마그네트론 10, 21 MeV의 에너지에서 95, 96% 의 투과율이 측정되었고 30 $^{\circ}$. 60 。각도의 경사로 빔이 전달될 때는 90.3, 94.4% 가 측정되었다. CCTV 카메라를 이용하여 흉부 및 복부의 움직임을 촬영한 영상을 Matlab프로그램으로 구현한 오차분석 프로그램을 적용한 결과, 환자 자세에 대한 오차의 평균값은 흉부의 lateral 방향에서는 3.63$\pm$1.4 mm, AP 방향에서는 2.1$\pm$0.82 mm이었다. 그리고 복부의 later의 방향에서는 7.0$\pm$2.1 mm, AP 방향에서는 6.5$\pm$2.2 mm 이었다. 또한 표적 위치측정을 위해서 환자의 피부에 임의의 가상표적을 부착하고 CT 촬영한 영상결과, 프레임으로 가상표 적에 대한 위치를 정확히 파악할 수 있었다. 결론 : 제작된 프레임을 적용하여 방사선투과율 측정실험, 환자 외부자세에 대한 오차 측정실험, 가상표적 위치측정 실험 등을 수행하였다. 환자 외부자세에 대한 오차 측정실험 경우, 더 많은 Volunteer를 적용하여 보다 정확한 오차 측정실험이 수행되어야 할 것이며 정확한 표적 위치 측정실험을 위해서 내부 마커를 삽입한 환자를 적용한 임상실험이 수행되어야 할 것이다. 또한 위치결정에서 획득한 좌표값의 정확성을 알아보기 위해서 팬톰을 이용한 방사선조사 실험이 추후에 실행되어져야 할 것이다. 그리고 제작된 프레임에 Rotating X선 시스템과 내부 장기의 움직임을 계량화하고 PTV에서의 최적 여유폭을 설정함으로써 정위 방사선수술 및 3 차원 업체 방사선치료에 대한 병소 위치측정과 환자의 자세에 대한 setup 오차측정 결정에 도움이 될 수 있을 것이라고 사료된다.

• Informatization Policy
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• v.27 no.2
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• pp.66-83
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• 2020

Local issues that occur in cities typically garner great attention from the public. While local governments strive to resolve these issues, it is often difficult to effectively eliminate them all, which leads to complaints. In tackling these issues, it is imperative for local governments to use big data to identify the nature of complaints, and proactively provide solutions. This study applies the LDA topic modeling technique to research and analyze trends and patterns in complaints filed online. To this end, 9,625 cases of online complaints submitted to the city of Busan from 2015 to 2017 were analyzed, and 20 topics were identified. From these topics, key topics were singled out, and through analysis of quarterly weighting trends, four "hot" topics(Bus stops, Taxi drivers, Praises, and Administrative handling) and four "cold" topics(CCTV installation, Bus routes, Park facilities including parking, and Festivities issues) were highlighted. The study conducted big data analysis for the identification of trends and patterns in civil affairs and makes an academic impact by encouraging follow-up research. Moreover, the text mining technique used for complaint analysis can be used for other projects requiring big data processing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.705-717
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• 2020

Cities in the world are rushing to develop smart cities to create a sustainable and happy city by solving many problems in cities using information and communication technologies such as big data and IoT. However, in Korea's smart cities and smart city certification systems, the focus is on platform-oriented hardware infrastructure, and the information security aspect is first considered to build and authenticate. It is a situation in which a response system for the risk of leakage of big data containing personal information is needed through policy research on the aspect of personal information protection for smart city operation. This paper analyzes the types of personal information in smart cities, problems associated with the construction and operation of smart cities, and the limitations of the current smart city law and personal information protection management system. As a solution, I would like to present a model of a personal information protection management system in the smart city field and propose a plan to strengthen personal information protection through this. Since the management system model of this paper is applied and operated in the national smart city pilot cities, demonstration cities, and CCTV integrated control centers, it is expected that citizens' personal information can be safely managed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2123-2130
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• 2015

For such automatic monitoring robot or a robot cleaner that is utilized indoors, if it deviates from someone by replacement or, or of a mobile robot such as collisions with unexpected object direction or planned path, based on the planned path There is a need to come back to, it is necessary to tough self-position estimation ability of mobile robot in this, which is also associated with resolution of the kidnap problem of conventional mobile robot. In this study, the case of a mobile robot, operates indoors, you want to take advantage of the low cost of the robot. Therefore, in this paper, by using the acquisition device to an external image information such as the CCTV which is installed in a room, it acquires the environment image and take advantage of marker recognition of the mobile robot at the same time and converted it absolutely spatial coordinates it is, we are trying to solve the self-position estimation of the mobile robot in the room and kidnap problem and actual implementation methods potential field to try utilizing robotic systems. Thus, by implementing the method proposed in this study to the actual robot system, and is promoting the relevant experiment was to verify the results.