• Title/Summary/Keyword: 영상취득시스템

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Performance Evaluation of LTE-VPN based Disaster Investigation System for Sharing Disaster Field Information (재난사고 정보공유를 위한 LTE-VPN기반 현장조사시스템 성능평가)

  • Kim, Seong Sam;Shin, Dong Yoon;Nho, Hyun Ju
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.602-609
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    • 2020
  • In the event of a large-scale disaster such as an earthquake, typhoon, landslide, and building collapse, the disaster situation awareness and timely disaster information sharing play a key role in the disaster response and decision-making stages for disaster management, such as disaster site control and evacuation of residents. In this paper, an exited field investigation system of NDMI (National Disaster Management Research Institute) was enhanced with an LTE-VPN- based wireless communication system to provide an effective on-site response in an urgent disaster situation and share observation data or analysis information acquired at the disaster fields in real-time. The required performance of wireless communication for the disaster field investigation system was then analyzed and evaluated. The experimental result for field data transmission performance of an advanced wireless communication investigation system showed that the UDP transmission performance of at least 4.1Mbps is required to ensure a seamless video conference system between disaster sites. In addition, a wireless communication bandwidth of approximately 10 Mbps should be guaranteed to smoothly share the communication and field data between the survey equipment currently mounted on the survey vehicle.

Laser Tracking Analysis of Space Debris using SOLT System at Mt. Gamak (감악산 SOLT 시스템을 이용한 우주잔해물 레이저추적 성능분석)

  • Lim, Hyung-Chul;Park, Jong-Uk;Kim, Dong-Jin;Seong, Kipyung;Ka, Neung-Hyun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.43 no.9
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    • pp.830-837
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    • 2015
  • Space debris has been a major issue recently for the space-active nations because its growing population is expected to increase the collision risk with operational satellites. Radar and electro-optical system has been used for space debris surveillance, which may cause unnecessary anti-collision manoeuvers due to their low tracking accuracy. So an additional tracking system is required to improve the predicted orbit accuracy and then to jude the anti-collision maneouvers more efficiently. The laser tracking system has been considered as an alternative to decrease these unnecessary manoeuvers. Korea Astronomy and Space Science Institute has been developing a space object laser tracking system which is capable of laser tracking for satellites with retro-reflectors and for space debris using high power laser, and satellite imaging using adaptive optics. In this study, the tracking capability is analyzed for space debris using high power laser based on link budget, false alarm probability and signal detection probability.

Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System (정밀도로지도 제작을 위한 모바일매핑시스템 기반 딥러닝 학습데이터의 자동 구축)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.133-139
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    • 2021
  • Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

Eyelid Detection Algorithm Based on Parabolic Hough Transform for Iris Recognition (홍채 인식을 위한 포물 허프 변환 기반 눈꺼풀 영역 검출 알고리즘)

  • Jang, Young-Kyoon;Kang, Byung-Jun;Park, Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.1
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    • pp.94-104
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    • 2007
  • Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.

Optical Multi-Normal Vector Based Iridescence BRDF Compression Method (광학적 다중 법선 벡터 기반 훈색(暈色)현상 BRDF 압축 기법)

  • Ryu, Sae-Woon;Lee, Sang-Hwa;Park, Jong-Il
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.3
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    • pp.184-193
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    • 2010
  • This paper proposes a biological iridescence BRDF(Bidirectional Reflectance Distribution Function) compression and rendering method. In the graphics technology, iridescence sometimes is named structure colors. The main features of these symptoms are shown transform of color and brightness by varying viewpoint. Graphics technology to render this is the BRDF technology. The BRDF methods enable realistic representation of varying view direction, but it requires a lot of computing power because of large data. In this paper, we obtain reflection map from iridescence BRDF, analyze color of reflection map and propose representation method by several colorfully concentric circle. The one concentric circle represents beam width of reflection ray by one normal vector. In this paper, we synthesize rough concentric by using several virtually optical normal vectors. And we obtain spectrum information from concentric circles passing through the center point. The proposed method enables IBR(image based rendering) technique which results is realistic illuminance and spectrum distribution by one texture from reduced BRDF data within spectrum.

Detection of Zebra-crossing Areas Based on Deep Learning with Combination of SegNet and ResNet (SegNet과 ResNet을 조합한 딥러닝에 기반한 횡단보도 영역 검출)

  • Liang, Han;Seo, Suyoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.141-148
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    • 2021
  • This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.

멀티빔 자료를 이용한 웹기반의 3차원 해저 지형 가시화

  • 노대훈;박요섭;김학일
    • Proceedings of the KSRS Conference
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    • 2000.04a
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    • pp.166-171
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    • 2000
  • 밀티빔 음향 측심기 (Multibeam Echo Sounder)는 탐사선에 수직방향으로 해저면을 주사(Swath)하여, 한번의 송수신(Ping)으로 다중의 빔자료를 얻을 수 있는 측심기로, 해저면에 반사되어 되돌아오는 음파의 음압을 기록하고, 사이드 스캔 소나 자료도 동시에 취득하는 기능을 가지고 있으므로, 측심된 해저 지형(Bathymetry)과 해저 지형을 덮고 있는 해저면의 퇴적 상황(Sediment Environment)도 동시에 얻을 수 있는 다목적 측심기이다. 본 논문에서는 L3사의 Sea Beam 2100 멀티빔 음향 측심기를 통해 얻은 자료를 처리하여, 3차원 공간 데이터인 DEM(Digital Elevation Model)을 생성하고, VRML을 이용한 웹상에서의 해저 지형 가시화를 통해, 세계 어느 곳에서나 웹을 통하여 쉽게 정보를 공유할 수 있는 3차원 해저 지리 정보 시스템의 구현을 목적으로 한다. 멀티빔 음향 측심기를 통해 얻어진 자료는 항해 자료 보정, 음속 보정, 빔 좌표 계산과 분리, 오측심 자료 제거, 조석 보정 등의 단계를 거쳐 측심자료의 정확도 및 신뢰도를 높이는 과정을 거치게 된다. 보정된 멀티빔 음향 측심자료는 무작위 점 사상(Point Topology)으로 산재 되어 있는 빔 자료를 임의의 단위영역으로 변환하는 과정을 거쳐야 하는데, 이 과정을 격자화라고 한다. 자료의 격자화를 통해 3차원 공강 데이터인 DEM 파일을 제작하고, 이 DEM 파일과 음압 영상을 이용해 웹상에서의 3차원 해저 지형의 가시화를 실현한다. 웹상에서의 3차원 지형 가시화에서 방대한 양의 지형 데이터는 데이터 전송 시간과 렌더링 시간에 치명적인 문제이다. 따라서, 렌더링 시간과 데이터 전송 시간을 단축시키기 위한, 지형 자료의 LOD(Level of Detail)를 통해, VRML을 이용한 보다 효과적인 웹상에서의 3차원 해저 지형의 가시화를 실현한다.면 기업은 고객으로 공간적인 제약으로 인한 불신을 불식시키는 신뢰감을 주게 된다. 이러한 고객서비스 향상과 물류비용 절감은 사이버 쇼핑몰이 전국 어디서나 우리의 안방에서 자연스럽게 점할 수 있는 상황을 만들 것이다.SP가 도입되어, 설계업무를 지원하기위한 기본적인 시스템 구조를 구상하게 된다. 이와 함께 IT Model을 구성하게 되는데, 객체지향적 접근 방법으로 Model을 생성하고 UML(Unified Modeling Language)을 Tool로 사용한다. 단계 4)는 Software Engineering 관점으로 접근한다. 이는 최종산물이라고 볼 수 있는 설계업무 지원 시스템을 Design하는 과정으로, 시스템에 사용될 데이터를 Design하는 과정과, 데이터를 기반으로 한 기능을 Design하는 과정으로 나눈다. 이를 통해 생성된 Model에 따라 최종적으로 Coding을 통하여 실제 시스템을 구축하게 된다.the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technological effects. Since the HAN projects consists of 18 subprograms, it is difficult In evaluate all the subprograms simultaneously. Despite, each program is being performed under the category of HAN projects, so the common soci

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Development of Greenhouse Environment Monitoring & Control System Based on Web and Smart Phone (웹과 스마트폰 기반의 온실 환경 제어 시스템 개발)

  • Kim, D.E.;Lee, W.Y.;Kang, D.H.;Kang, I.C.;Hong, S.J.;Woo, Y.H.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.18 no.1
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    • pp.101-112
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    • 2016
  • Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.

The Design of Cardiovascular System Model Equipment for Education (심장 혈관계 시스템의 교육 모형 고안)

  • Won, Doyeon;Jung, Hongmoon;Jung, Jaeeun;Lee, Joonha
    • Journal of the Korean Society of Radiology
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    • v.8 no.3
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    • pp.117-121
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    • 2014
  • The understanding of medical knowledge regarding cardiac shape and cardiovascular system is essentially required for a medical personnel as well as a medical technician. Correct acquisition of medical knowledge through cardiac miniature model is very critical because it is directly related to a patient life. therefore replica model is necessary for the education regarding cardiac and cardiovascular system. In this study anatomical cardiovascular system on fluoroscopy can be shown by cardiac and cardiovascular fluoroscopy replica model. Also, it helps to understand a cardiovascular radiograph. Consequentially medical personnel and medical technician are able to take advantage of this equipment to understand cardiovascular fluoroscopy system.

A Study on Automatic Detection of Speed Bump by using Mathematical Morphology Image Filters while Driving (수학적 형태학 처리를 통한 주행 중 과속 방지턱 자동 탐지 방안)

  • Joo, Yong Jin;Hahm, Chang Hahk
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.55-62
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    • 2013
  • This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).