• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.139-146
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• 2017

A ground moving target's velocity estimation algorithm applicable for a SAR-GMTI system using 2 channel displaced phase center antenna(DPCA) is proposed. In this algorithm, we assume target's across-track velocity can be estimated by along-track interferometry (ATI) and present a method to estimate target's along-track velocity. To accomplish this method, we first transform a radar-target geometry in which a moving target has zero velocity via altering a radar velocity such that target's velocity is reflected into it and next manipulate the spectral centers of the subapertures within the synthetic aperture. The validity of the proposed algorithm is demonstrated through simulation results showing the performance of the target's velocity estimation and the enhancement of reconstructed target image quality in terms of resolution and SINR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.773-781
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• 2013

The Hough transform for line detection is widely used in many machine vision applications due to its robustness against data loss and distortion. However, it is not appropriate for real-time embedded vision systems, because it has inefficient computation structure and demands a large number of memory accesses. Thus, this paper proposes an improved voting scheme of the Hough transform, and then applies this scheme to a Hough transform hardware architecture so that it can provide real-time performance with less hardware resource. The proposed voting scheme reduces computation overhead of the voting procedure using correlation between adjacent pixels, and improves computational efficiency by increasing reusability of vote values. The proposed hardware architecture, which adopts this improved scheme, maximizes its throughput by computing and storing vote values for many adjacent pixels in parallel. This parallelization for throughput improvement is accomplished with little hardware overhead compared with sequential computation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.9
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• pp.111-119
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• 2008

As the penetration of distributed generation systems is recently high, there have been metering errors, trips of protective devices in KEPCO distribution systems including an occurrence of false fault-indicator in distribution automation system. The cause of malfunctions was the reverse-power-flow phenomenon due to transformer wiring types. By the effect of the reverse-power-flow, each of phase's fundamental currents was added by about 3 times on the neutral line. A new method based on the analysis of the reverse-power-flow is proposed in this paper. Fault currents on each section were analyzed by the proposed method, and the effect of types of transformer wiring was examined experimentally. In order to reduce the malfunctions due to the reverse-power-flow, controlling the zero-sequence impedance of transformer was designed and verified by using PSCAD/EMTDC software.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.129-129
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• 2010

적외선 검출소자(Infrared Photodetector)는 근적외선에서 원적외선 영역에 이르는 광범위한 파장 범위의 적외선을 이용하는 기기로서 대상물이 방사하는 적외선 영역의 에너지를 흡수하여 이를 영상화할 수 있는 장비이다. 적외선 관련 기술은 2차 세계대전 기간에 태동하였으며, 현재에는 원거리 감지기술 등과 접목되면서 그 활용 분야가 다양해지고 있다. 특히 능동형 정밀 타격무기를 비롯한 감시 정찰 장비 및 지능형 전투 장비 시스템 등에 대한 요구를 바탕으로 보다 정밀하고 신속한 표적 감지 및 정보처리 기술에 관한 연구가 선진국을 통해서 활발히 진행되고 있다. 기존의 Bolometer 형식의 열 감지 소자는 반응 속도가 느리고 측정 감도가 낮은 단점이 있으며, MCT(HgCdTe)를 이용한 적외선 검출기의 경우 높은 기계적 결함과 77K 저온에서 동작해야하기 때문에 발생하는 추가 비용 등이 문제점으로 지적되고 있다[1]. 이에 반해 화합물 반도체 자기조립 양자점(self-assembled quantum dot)을 이용한 적외선 수광소자는 양자점이 가지는 불연속적인 내부 에너지 준위로 인하여, 높은 내부 양자 효율과 온도 안정성을 기대할 수 있으며, 고성능, 고속처리, 저소비전력 및 저소음의 실현이 가능하다. 본 연구에서는 적층 InAs/InGaAs dot-in-a-well 구조를 유기금속화학기상증착법을 이용하여 성장하고 이를 소자에 응용하였다. 균일한 적층 양자점의 성장을 위해서 원자현미경(atomic force microscopy)을 이용하여, 각 층의 양자점의 크기와 밀도를 관찰하였고, photoluminescence (PL)를 이용하여 발광특성을 연구하였다. 각 층간의 GaAs space layer의 두께와 온도 조절 과정을 조절함으로써 균일한 적층 양자점 구조를 얻을 수 있었다. 이를 이용하여 양자점의 전도대 내부의 에너지 준위간 천이(intersubband transition)를 이용하는 n-type GaAs/intrinsic InAs 양자점/n-type GaAs 구조의 양자점 적외선수광소자 구조를 성장하였다. 이 과정에서 상부 n-type GaAs의 성장 온도가 600도 이상이 되는 경우 발광효율이 급격히 감소하고, 암전류가 크게 증가하는 것을 관찰하였다. 이는 InAs 양자점과 주변 GaAs 간의 열에 의한 상호 확산에 의하여 양자점의 전자 구속 효과를 저해하는 것으로 설명된다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.197-203
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• 2015

Nuclear power plant has increased continuously for power production in all over the world and the interest about nuclear accident and the dismantling of aging nuclear power plant has been a growing. The leaked radioactive source that is generated by radiation accidents must detect and remove to minimized the damage as soon as possible. Gamma-ray detection system that have been developed until now cannot provide the precise position of radioactive sources because they detect and imaging the position of radiation sources in just two dimensions. In this paper, stereo gamma ray detection system has developed and the algorithm for calculation of the distance has implemented to be able to measure the distribution of the leakage gamma ray source for the system. Stereo camera calibration for distance detection was conducted with the correction pattern and LED light and we carried out performance test of the system for the LED light source and a gamma ray source. In both experiments the results of the performance test, it was confirmed to have a 5% error. The results of this paper is used as a material for the development of gamma-ray imaging device.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.11
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• pp.1133-1144
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• 2019

Recently, the amount of image on the Internet has rapidly increased, due to the advancement of smart devices and various approaches to effective image retrieval have been researched under these situation. Existing image retrieval methods simply detect the objects in a image and carry out image retrieval based on the label of each object. Therefore, the semantic gap occurs between the image desired by a user and the image obtained from the retrieval result. To reduce the semantic gap in image retrievals, we connect the module for multiple objects classification based on deep learning with the module for human behavior classification. And we combine the connected modules with a behavior ontology. That is to say, we propose an image retrieval system considering the relationship between objects by using the combination of deep learning and behavior ontology. We analyzed the experiment results using walking and running data to take into account dynamic behaviors in images. The proposed method can be extended to the study of automatic annotation generation of images that can improve the accuracy of image retrieval results.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.441-447
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• 2018

This study aims to develop digital techniques that enable repeated practice of dental radiography using augmented reality technology. A three-dimensional object was fabricated by superimposing a photograph of an adult model and a computed tomography image of a manikin phantom. The system was structured using 106 radiographs such that one of these saved radiographs is opened when the user attempts to take a radiograph on a mobile device. This system enabled users to repeatedly practice at the pre-clinical stage without exposure to radiation. We attempt to contribute to enhancing dental hygienists' competency in dental radiography using these techniques. However, a system that enables the user to actually take a radiograph based on face recognition would be more useful in terms of practice, so additional studies are needed on the topic.

• Journal of IKEEE
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• v.22 no.4
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• pp.970-977
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• 2018

The autonomous vehicle is based on an advanced driver assistance system (ADAS) consisting of a sensor that collects information about the surrounding environment and a control module that determines the measured data. As interest in autonomous navigation technology grows recently, an easy development framework for ADAS beginners and learners is needed. However, existing development and verification methods are based on high performance vehicle simulator, which has drawbacks such as complexity of verification method and high cost. Also, most of the schemes do not provide the sensing data required by the ADAS directly from the simulator, which limits verification reliability. In this paper, we present an interactive ADAS development and verification framework using a 3D vehicle simulator that overcomes the problems of existing methods. ADAS with image recognition based artificial intelligence was implemented as a virtual sensor in a 3D car simulator, and autonomous driving verification was performed in real scenarios.

• Informatization Policy
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• v.26 no.1
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• pp.46-61
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• 2019

The Fourth Industrial Revolution has been revolutionizing industry and education. This paper proposes an education platform, Smart Space EduPlatform (SSEP), for the real estate industry, aimed at educating the basic real estate technology (RETech) for workers in the real estate industry so they can achieve the highest and best use of the real estate in the smart environment. The habitat of SSEP is driven by the donation system ensuring sustainability, various technical functions such as tools for content production and learning participation, and learning behavior frameworks each in form of a learner, a teacher, and a helper. Services of SSEP consist of 17 important RETech lectures under 6 categories-planning and design, decision-making, management, economics, construction, and equipment-and project-based learning (PBL) curriculums. The lectures are provided along with video contents, additional learning materials and learning management service, while teachers' workshops, learner invitation and registration management, curriculum operation services are offered for the PBL curriculums.