• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.907-908
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• 2006

We describe a method for localizing a mobile robot in its working environment using a vision system and Virtual Reality Modeling Language (VRML). The robot identifies landmarks in the environment, using image processing and neural network pattern matching techniques, and then its performs self-positioning with a vision system based on a well-known localization algorithm. After the self-positioning procedure, the 2-D scene of the vision is overlaid with the VRML scene. This paper describes how to realize the self-positioning, and shows the overlap between the 2-D and VRML scenes. The method successfully defines a robot's path.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05c
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• pp.17-20
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• 2004

PV model is presented based on the shockley diode equation. The simple model has a photo-current source, an single diode junction and a series resistance and includes temperature dependences. An accurate PV module electrical model is presented, matching with boost converter MPPT strategy and demosntarted in Matlab for a typical general purpose solar cell. Given solar insolation and temperature, the model returns current vector and MPP.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.193-198
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• 2015

A large number of vision applications rely on matching keypoints across images. Pedestrian detection is under constant pressure to increase both its quality and speed. Such progress allows for new application. A higher speed enables its inclusion into large systems with extensive subsequent processing, and its deployment in computationally constrained scenarios. In this paper, we focus on improving the speed of pedestrian detection using HOG(histogram of oriented gradient) and multi frame operation which is robust to illumination changes in cluttering images. The result of our simulation indicates that the detection rate and speed of the proposed method is much faster than that of conventional HOG and differential images.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.487-494
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• 1986

This paper is concerned with the techniques of error check and reduction of state diagram using logic programming. Error check program aims to check not only syntax errors but also semantic errors. And reduction program optimizes the state diagram by finding the redundant equivalence states and removing those from the set of states. The input of both program is state diagram represented as state table form. The output of error check program is error comment. The output of reduction program is equivalence reduced state table. Both programs are implemented using prolog. Prolog has very powerful pattern matching, and its automatic back-tracking capabilities facilitate easy-to-write error check and reduction programs.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.215-218
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• 2002

Gesture recognitions needed for various applications and is now gaining in importance as one method of enabling natural and intuitive human machine communication. In this paper, we propose a real time hand-signal recognition system in 3-dimensional space performs robust, real-time tracking under varying illumination. As compared with the existing method using classical pattern matching, this system is efficient with respect to speed and also presents more systematic way of defining hand-signals and developing a hand-signal recognition system. In order to verify the proposed method, we developed a virtual driving system operated by hand-signals.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.25-31
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• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.331-334
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• 1993

It is a standard problem that designs a controller to minimize the $H_{\infty}$-norm of a given plant. By reducing a standard problem to a model-matching problem, we can obtain all the parameters which consist of a controller. After presenting a practical model and applying it to a tracking model, we design an $H_{\infty}$ controller and an LQ controller to concrete that $H_{\infty}$ control theory is far more robust than LQ control theory. And we show the advantage of an $H_{\infty}$ controller by obtaining a desired Bode diagram and comparing it with that of an LQ controller.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.260-270
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• 2023

We introduce a novel Visual Inertial Odometry (VIO) algorithm designed to improve the performance of thermal-inertial odometry. Thermal infrared image, though advantageous for feature extraction in low-light conditions, typically suffers from a high noise level and significant information loss during the 8-bit conversion. Our algorithm overcomes these limitations by approximating a 14-bit raw pixel histogram into a Gaussian mixture model. The conversion method effectively emphasizes image regions where texture for visual tracking is abundant while reduces unnecessary background information. We incorporate the robust learning-based feature extraction and matching methods, SuperPoint and SuperGlue, and zero velocity detection module to further reduce the uncertainty of visual odometry. Tested across various datasets, the proposed algorithm shows improved performance compared to other state-of-the-art VIO algorithms, paving the way for robust thermal-inertial odometry.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.67-80
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• 2006

In this paper, we propose a new pointing device that is replaced a mouse as the pointing device with. For reducing the existing pointing device's problem which had marker and high-cost, we develop a new pointing device using computer vision like as a similar human vision system. The proposed system first carries out a real-time movement tracking system using image data which are segmented by color modeling, and finally does the pointing action by 3-D coordinate calculated from stereo geometry information resulting from stereo matching of the segmented region.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.185-188
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• 2015

미리 저장된 객체의 3차원 특징점(Feature point) 좌표와 카메라 영상의 2차원 특징점 좌표를 매칭(Matching)하여 객체를 추적하는 방식의 경우, 카메라의 시점이 변할 때 특징점에서 발생되는 원근 효과(Perspective effect)가 반영되지 못하여 특징점 매칭 오류가 발생한다. 따라서 특징점에서 발생하는 원근 효과를 반영하여 정확한 카메라 포즈를 추정하기 위해 이전 프레임(Frame)의 카메라 포즈(Camera Pose)에 맞추어 텍스쳐가 포함 된 3차원 객체의 모델을 렌더링 하여 원근 효과를 적용한 후, 현재 카메라 영상과 특징점 매칭하여 프레임 사이의 카메라 움직임을 구하여 객체를 추적한다. 더 나아가 본 논문에서는 특징점 매칭에서 발생하는 작은 오류들로 인한 미세한 카메라 움직임은 2단계의 임계치(Threshold)를 적용하여 떨림 현상으로 간주하여 떨림 현상이 제거된 객체 추적을 수행한다. 매 프레임마다 카메라 포즈에 맞춘 추적 객체를 렌더링 하기 때문에 떨림 현상으로 간주되어 제거된 카메라 움직임은 누적되지 않고, 추적 오류도 발생시키지 않는다.