• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1039-1040
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• 2008

Multi-resolution approach to object detection wherein all entities including the partial information and background knowledge are modeled in set-theoretic terms whereby associated processing are formulated via set-theoretic operations is investigated. The generic set-theoretic paradigm is then applied to particular problems of detecting malfunctions in semiconductor fabrication process wherein the computational- and storage- efficiencies as enabled by morphological signal processing further coupled with flexibilities enabled by multi-resolution approach leads to a scalable paradigm in which the desired performance can be obtained on-demand fashion.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.894-899
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• 2000

Optimization of 26 design variables selected from suspension characteristics for Korean High Speed Train (KHST) is performed according to the minimization of 58 responses which represent running safety and ride comfort for KHST and analyzed by using the each response surface model from stochastic design experiments. Sensitivity of design variables is also analyzed through the response surface model which ineffective design prameters to the performance index are screened by using stepwise regression method. The response surface models are used for optimizing design variables through simplex algorism. Values of performance index simulated by optimized design parameters are totally lower than those by initial design parameters. It shows that this method is effective for optimizing multi-design variables to multi-object function.

• 제어로봇시스템학회논문지
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• 제19권10호
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• pp.886-890
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• 2013

In this paper, a 3D coordinates acquisition method for a mechanical assembly is developed by using multiview X-ray images. The multi-view X-ray images of an object are obtained by a rotary table. From the rotation transformation, it is possible to obtain the 3D coordinates of corresponding edge points on multi-view X-ray images by triangulation. The edge detection algorithm in this paper is based on the attenuation characteristic of the X-ray. The 3D coordinates of the object points are represented on a graphic display, which is used for the inspection of a mechanical assembly.

• 전기학회논문지
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• 제62권1호
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• pp.43-48
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• 2013

In this paper, magnetic buoyancy force on nonmagnetic solid object submerged in magnetic liquid was simulated and measured. For the evaluation of the force, a multi-physics approach of hydrostatic equilibrium considering magnetic body force as well as gravity is presented. The magnetic body force should be regarded as an additional forcing term in the momentum equation of hydrodynamics. It is also shown that the virtual air-gap based Kelvin's force formula is a useful method for the calculation of force distribution in the magnetic liquid. The experimental result which was performed by a load-cell measurement system agreed quantitatively well with the numerical one.

• 한국멀티미디어학회논문지
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• 제22권10호
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• pp.1149-1159
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• 2019

We present a novel deep learning architecture for obtaining a latent image from a single blurry image, which contains dynamic motion blurs through object/camera movements. The proposed architecture consists of two sub-modules: blur image restoration and optical flow estimation. The tasks are highly related in that object/camera movements make cause blurry artifacts, whereas they are estimated through optical flow. The ablation study demonstrates that training multi-task architecture simultaneously improves both tasks compared to handling them separately. Objective and subjective evaluations show that our method outperforms the state-of-the-arts deep learning based techniques.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.1006-1018
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• 2020

Dataset is getting more import to develop a learning based algorithm. Quality of the algorithm definitely depends on dataset. So we introduce new dataset over 200 thousands images which are fully labeled multi modal sensor data. Proposed dataset was designed and constructed for researchers who want to develop detection, tracking, and action classification in outdoor environment for surveillance scenarios. The dataset includes various images and multi modal sensor data under different weather and lighting condition. Therefor, we hope it will be very helpful to develop more robust algorithm for systems equipped with difference kinds of sensors in outdoor application. Case studies with the proposed dataset are also discussed in this paper.

• 제어로봇시스템학회논문지
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• 제10권4호
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• pp.350-356
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• 2004

This paper presents a farce manipulability analysis of multi-legged walking robots, which calculates force or acceleration workspace attainable from joint torque limits of each leg. Based on the observation that the kinematic structure of the multi-legged walking robots is basically the same as that of multiple cooperating robots, we derive the proposed method of analyzing the force manipulability of walking robot. The force acting on the object in multiple cooperating robot systems is taken as reaction force from ground to each robot foot in multi-legged walking robots, which is converted to the force of the body of walking robot by the nature of the reaction force. Note that each joint torque in multiple cooperating robot systems is transformed to the workspace of force or acceleration of the object manipulated by the robots in task space through the Jacobian matrix and grasp matrix. Assuming the torque limits are given in infinite norm-sense, the resultant dynamic manipulability is derived as a polytope. The validity of proposed method is verified by several examples, and the proposed method is believed to be useful for the optimal posture planning and gait planning of walking robots.

• 한국항행학회논문지
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• 제16권2호
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• pp.386-393
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• 2012

본 논문에서는 객체의 관심점(interest points)에 대한 지역 특징 기술자를 이용하여 이미지나 동영상에서 다수의 관심 객체를 효과적으로 인식하고 추적하기 위한 기법을 제안한다. 이를 위해 먼저 대상이 되는 객체를 포함하는 다양한 이미지를 수집하고 SURF 알고리즘을 적용하여 객체의 관심점과 그들에 대한 지역 특징 기술자를 생성한다. 지역 특징에 대한 통계적인 분석을 통하여 관심점들 중에서 해당 객체의 특성을 가장 잘 표현하는 대표점(representative points)을 선택하고 이를 바탕으로 이미지에 존재하는 객체를 인식한다. 또한, 지역 특징 기술자의 정합을 응용하여 각 SURF 지점들의 움직임 벡터를 생성하고 이를 기반으로 실시간으로 객체를 추적한다. 제안하는 기법은 모든 객체를 독립적으로 다루기 때문에, 여러 개의 객체를 동시에 인식하고 추적할 수 있다. 다양한 실험을 통해, 동영상에서 객체의 존재 여부 및 종류를 신속하게 판별하고 관심 객체의 추적을 효과적으로 수행할 수 있음을 보인다.