• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.449-451
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• 1998

컴퓨터 비젼에서의 여러 문제를 해결하는데 있어서 최소화 기법이 많이 사용되지만 구체적인 구현 방법이나 성능 평가에 대한 자료가 미흡하다. 본 논문에서는 다른 연구자들이 기법을 선택하는데 참고가 되도록 널리 사용되는 최소화 기법들의 방법, 구현, 성능 등에 관하여 기술한다.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.21-29
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• 2003

It is very important to reduce the computational time in estimating the parameters of vision control algorithm for robot's position control in real time. Unfortunately, the batch estimation commonly used requires too murk computational time because it is iteration method. So, the batch estimation has difficulty for robot's position control in real time. On the other hand, the Extended Kalman Filtering(EKF) has many advantages to calculate the parameters of vision system in that it is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm for the robot's vision control in real time. The vision system model used in this study involves six parameters to account for the inner(orientation, focal length etc) and outer (the relative location between robot and camera) parameters of camera. Then, EKF has been first applied to estimate these parameters, and then with these estimated parameters, also to estimate the robot's joint angles used for robot's operation. finally, the practicality of vision control scheme based on the EKF has been experimentally verified by performing the robot's position control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.3
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• pp.305-315
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• 2016

This study aims to develop a robot vision control scheme using the Newton-Raphson (N-R) method for the uncertainty of circumstance caused by the appearance of obstacles during robot movement. The vision system model used for this study involves six camera parameters (C1-C6). First, the estimation scheme for the six camera parameters is developed. Then, based on the six estimated parameters for three of the cameras, a scheme for the robot's joint angles is developed for the placement of a slender bar. For the placement of a slender bar for the uncertainty of circumstances, in particular, the discontinuous robot trajectory caused by obstacles is divided into three obstacle regions: the beginning region, middle region, and near-target region. Then, the effects of obstacles while using the proposed robot vision control scheme are investigated in each obstacle region by performing experiments with the placement of the slender bar.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.504-507
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• 2005

In this paper, we propose a calibration technique of 3D coordinates using orthogonal stereo vision. First, we acquire front- image and upper- image from stereo cameras with real time and extract each coordinates of a moving object using differential operation and ART2 clustering algorithm. Then, we can generate 3D coordinates of that moving object through combining these two coordinates. Finally, we calibrate 3D coordinates using orthogonal stereo vision since 3D coordinates are not accurate due to perspective. Experimental results show that accurate 3D coordinates of a moving object can be generated by the proposed calibration technique.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.872-898
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• 2007

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.903-909
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• 2018

In this paper, performance analysis of machine vision techniques is presented to improve the convenience and speed of automatic inspection in the industrial field when machine vision is applied to the image not taken in the stationary state, but in the moving state on a conveyer. When the length of cylindrical rods used for automobiles was measured using the edge detection method, the conveying speed increased, and the uncertainty of the boundary between the background and the part image increased, which resulted in a shorter image of the object taken. This paper proposes a linear compensation method to predict the biased errors of the length measurements after examining the pattern of biased and random errors, respectively, with 6 different types of specimens and 7 velocity stages. The length measurement corrected by the linear compensation method had the same accuracy as the stationary state within the speed range of 30 cm/s and could enhance the application capability in automatic inspections.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.2
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• pp.110-116
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• 2005

It is very important to reduce the computational processing time for the application of the vision system in real time such as inspection, the determination of object's dimension and welding etc, because the vision system model involves a lot of measurement data acquired by CCD camera. Also, a lot of computation time is required in estimating the parameters in the vision system model if the iterative batch estimation method such as Newton Raphson is used. Thus, the effective computation method such as the Extended Kalman Filtering(EKF) is required to solve the above problems. The EKF has much advantages in that it takes explicitly into account the measurement uncertainties, and is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm to compute the parameters in the vision system model in real time. This vision system model involves the six parameters to account for the cameras inner and outer parameters. Also the EKF is applied to estimate the object's dimension. Finally, practicality of the estimation scheme of the vision system based on the EKF is verified experimently by performing the estimation of object's dimension.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1813-1819
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• 2011

In this research, the location positioning system supposed is concerned with range recognition technology using phase and magnitude of radio wave and adding technology of image histogram by vision. By the proposed technology, we design the radio transmitter and receiver and realize the measurement system, and save the data in disk that is earned from 900Mhz RF signal, middle frequency 450Khz of analog signal. Range information is earned the data through digital signal processing of IF signal. For the estimation of range measured, we analyze the difference between real range and measurement range, and also suggest the method to improve the measurement error using average processing and amplitude properties.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.560-566
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• 2005

In this paper, a practical technique for correction of a distorted image for vision-based localization of ubiquitous mobile robot. The localization of mobile robot is essential and is realized by using camera vision system. In order to wide the view angle of camera, the vision system includes a fish-eye lens, which distorts the image. Because a mobile robot moves rapidly, the image processing should he fast to recognize the localization. Thus, we propose the practical correction technique for a distorted image, verify the Performance by experimental test.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.386-394
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• 2011

This paper is concerned with the application of the vision control scheme for robot's point placement task in discontinuous trajectory caused by obstacle. The proposed vision control scheme consists of four models, which are the robot's kinematic model, vision system model, 6-parameters estimation model, and robot's joint angles estimation model. For this study, the discontinuous trajectory by obstacle is divided into two obstacle regions. Each obstacle region consists of 3 cases, according to the variation of number of cameras that can not acquire the vision data. Then, the effects of number of cameras on the proposed robot's vision control scheme are investigated in each obstacle region. Finally, the practicality of the proposed robot's vision control scheme is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.