• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.477-486
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• 2016

This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.118-131
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• 1991

The effects of free surface on vortex shedding phenomena around a bluff body were studied by both numerical simulation and flow visualization experiments. A vortex method, which approximates the vorticity field as the sum of discrete vortices; was used for the numerical simulation. Flow visualization experiments were performed in the KRISO cavitation tunnel. Hydrogen bubble was used as illumination material. Free surface elevation was also measured during experiments. The hydrodynamic drag and lift were predicted by numerical simulation. The predicted period of vortex shedding was compared with the results of experiments.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.214.1-214.1
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• 2012

한국천문연구원은 우주물체 전자광학 감시체계 기술개발 사업을 통해 자국위성의 추적감시를 위해 0.5m 광시야 감시관측소 국제 네트워크(OWL : Optical Wide-Field patroL)를 구축할 예정이다. OWL 시스템의 설계 검증을 위해 시험모델을 개발하였고, 연구소 내에 테스트베드에 설치하여 종합적인 테스트를 수행하고 있다. OWL 시험모델은 해외 설치모델과 동일하게 제작하였으며 돔을 제외한 모든 서브시스템을 국산화하였다. 유효구경 0.5m의 Richey-Cretian 형식의 광학계로 1.75도의 광시야를 구현하였고 영상보정을 위해 5개의 보정 렌즈를 사용하였다. 인공위성 추적을 위해 초당 10도 이상 기동이 가능한 alt-az 방식의 마운트를 개발하였다. 단일 노출에서 다수의 인공위성 궤적을 얻기 위해 chopper 제어 시스템을 도입하였고, chopper, 필터휠, de-rotator, CCD 카메라 등 4개의 부분품을 하나로 묶어 간결한 back-end를 구성하였다. 시스템의 안정성 향상과 유지보수의 용이성을 위해 망원경 및 관측소 제어 전용보드를 개발하였고, 전자동 무인관측을 위한 스케줄러 및 운영소프트웨어를 개발하였다. 시험모델을 이용하여 수 개월간 테스트을 수행하고, 관측결과 분석을 통하여 문제점을 수정보완한 후 OWL 시스템의 최종 설계안을 확정할 예정이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2799-2804
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• 2014

In this paper, we suggest three-dimensional information extraction map system using integral imaging technique. Integral imaging can record multiple elemental images with different perspectives using a 2D image acquisition device with lenslet array. Using these images, integral imaging can obtain 3D information and display 3D image. In this paper, the position difference between elemental images can be obtained using summation of absolute difference (SAD), and then 3D information can be extracted. Therefore, this technique can find the height information of 3D objects.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.118-122
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• 2020

문화재 영상 데이터는 방대한 양으로 인해 고해상도로 모두 저장이 어렵거나 시간이 지나 상대적으로 화질이 낮은 영상들이 다수 존재하기에 초해상화가 필요한 상황이 많다. 따라서 본 논문에서 처음으로 문화재 영상에 특화된 4 배 및 8 배 딥러닝 기반 초해상화 방식을 제안한다. 문화재 영상 데이터는 배경이 단조롭고 물체가 영상 중간에 위치한다는 특징이 있어 이를 고려해 중간 부분에서만 패치를 추출하는 방식을 적용하여 의미 있는 패치로 학습이 되도록 한다. 또 자연 영상 데이터 셋인 DIV2K 를 사용해 학습하는 방식과 직접 구성한 문화재 데이터 셋을 이용해 학습하는 방식, 그 둘을 적절히 함께 사용하여 학습하는 전이 학습 방법까지 세 가지로 학습하여 초해상화의 성능을 향상시키는 방법을 제안한다. 그 결과, 쌍삼차 보간법(Bicubic interpolation)보다 4 배 초해상화에서는 약 1.25dB, 8 배 초해상화에서는 약 1.26dB 의 성능 개선을 확인하였으며, 단순 DIV2K 로 학습한 방식보다는 4 배에서는 0.06dB, 8 배에서는 0.17dB 의 성능 개선을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.374-375
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• 2022

Recently, Metaverse service has been widely used to naturally communicate with a remote location, freeing from time and spatial constraints. In order to produce such contents, it is necessary to restore and synthesize a 3D model based on real space data. In this paper, a 3D-generated reconstruction model is produced based on continuous images using multiple cameras and a technique to correct the reconstructed 3D model is presented. For this. offline multi-camera setup was performed, errors were analyzed on the 3D model created through images obtained from various angles, and correction was performed using a matching technique between image frames. It is expected that 3D reconstructed data can be utilized in various service fields such as culture, tourism, and medical care.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1309-1315
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• 2014

The switch for a maglev vehicle should be designed such that the vehicle safely changes its track without touching the guiderail. In particular, a medium-to-low-speed EMS -type maglev train relies heavily on a U-type electromagnet where it generates levitation force and guidance force simultaneously. Therefore, it is necessary to evaluate the safety of the vehicle whenever it passes the switch, as it lacks active control of the guidance force. Furthermore, when the vehicle passes a segmented switch, which is a group of curves made up of connected lines with a small radius of curvature, it may come into mechanical contact with the guiderail owing to the excessive lateral displacement of the electromagnet. The goal of this study is to analyze the influence of a segmented switch on the safety of major design-related variables for achieving improved running safety. We propose a three-dimensional multibody dynamics model composed of two cars with one body. Using the proposed model, we perform a simulation of the lateral air gap, which is one of the measurements of the running safety of the vehicle when it passes the switch. The analyzed design variables are the length between short span girder, the articulation angle, the length between two centers of a fixed girder at its ends, and the number of girders. On the basis of the effects of the considered design variables, we establish an optimized design of a switch with improved safety.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.3
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• pp.18-27
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• 2002

In order to improve the accuracy of the solution near the boundary in an analysis of viscous flow around an arbitrary boundary which move and be deformed using an Eulerian concept, a level-set based grid deformation method is introduced to concentrate grid points near the boundary. This paper presents a new monitor function which can easily control the level of the concentration of grid points along the boundary. Computations for steady flow around a semi-circular cylinder mounted on the bottom of the flow domain were carried out to check the improvement of the solution using the adaptive grid system with an immersed boundary method. The present numerical results show a good agreement with the solutions obtained by a body fitted grid system and more accurate solutions than those computed with non-adaptive grid system. For the validation of mechanical usefulness of the present method, an expanded analysis of flow around multi-body fixed in the flow domain was carried out. Finally, the present moving adaptive grid method was applied to a two-dimensional bubble rise problem. The computed results show well adapted grid points around the boundary of the bubble at every time and a good agreement with the result calculated by fixed grid system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.111-121
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• 2011

Intelligent video analysis systems require techniques which can predict accidents and provide alarms to the monitoring personnel. In this paper, we present an abnormal behavior analysis technique based on adaptive background generation. More specifically, abnormal behaviors include fence climbing, abandoned objects, fainting persons, and loitering persons. The proposed video analysis system consists of (i) background generation and (ii) abnormal behavior analysis modules. For robust background generation, the proposed system updates static regions by detecting motion changes at each frame. In addition, noise and shadow removal steps are also were added to improve the accuracy of the object detection. The abnormal behavior analysis module extracts object information, such as centroid, silhouette, size, and trajectory. As the result of the behavior analysis function objects' behavior is configured and analyzed based on the a priori specified scenarios, such as fence climbing, abandoning objects, fainting, and loitering. In the experimental results, the proposed system was able to detect the moving object and analyze the abnormal behavior in complex environments.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.