• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.119-126
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• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.115-124
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• 2002

This paper presents an active auxiliary edge-resonant DC link snubber with a ringing surge damper and a three-phase voltage source type zero voltage soft-switching inverter with the resonat snubber treated here for the AC servo motor driver applications. The operation of the active auxiliary edge-resonant DC link snubber circuit with PWM voltage is described, together with the practical design method to select its circuit parameters. The three-phase voltage source type soft-switching inverter with a single edge-resonant DC link snubber treated here is evaluated and discussed for the small-scale permanent magnet (PM) type-AC servo motor driver from an experimental point of view. In addition to these, the AC motor stator current and its motor speed response for the proposed three-phase soft-switching inverter employing Intelligent Power Module(IPM) based on IGBTS are compared with those of the conventional three-phase hard-switching inverter using IPM. The practical effectiveness of the three-phase soft-switching inverter-fed permanent magnet type AC motor speed tracking servo driver is proven on the basis of the common mode current in a novel type three-phase soft-switching inverter-fed AC motor side and the conductive noise on the mains terminal interface voltage as compared with those of the conventional three-phase hard-switching inverter-fed permanent magnet type AC servo motor driver for the speed tracking applications.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.37-46
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• 2010

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.24-32
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• 2010

In this study, we have proposed a pre-processing algorithm newly developed for improving the tracking efficiency of the optical flow method. The developed pre-processing algorithm consists of a median filter, binarization, morphology, canny edge, contour detecting and an approximation method. In order to evaluate whether the optical flow tracking capacity increases, this study applied the pre-processing algorithm to the Lucas-Kanade(LK) optical flow algorithm, and comparatively analyzed its images and tracking results with those of optical flow without the pre-processing algorithm and with the existing pre-processing algorithm(composed of median filter and histogram equalization). As a result, it was observed that the tracking performance derived from the LK optical flow algorithm with the pre-processing algorithm, shows better tracking accuracy, compared to the one without the pre-processing algorithm and the one with the existing pre-processing algorithm. It seems to have resulted by successful segmentation for characteristic areas and subdivision into inner and outer contour lines.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.1-7
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• 2017

In this paper, we propose an efficient method that is tracking an object in real time using particle filter and adaptive observation model. When tracking object, it happens object shape variation by camera or object movement in variety environments. The traditional method has an error of tracking from these variation, because it has fixed observation model about the selected object by the user in the initial frame. In order to overcome these problems, we propose a method that updates the observation model by calculating the similarity between the used observation model and the eight-way of edge model from the current position. If the similarity is higher than the threshold value, tracking the object using updated observation model to reset observation model. On the contrary to this, the algorithm which consists of a process is to maintain the used observation model. Finally, this paper demonstrates the performance of the stable tracking through comparison with the traditional method by using a number of experimental data.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.100-105
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• 1998

Image processing was used to recognize parts at various disposition. Non-transpatent tachometer panel for automobile and semi-transparent panel have been used as test specimen. Laplacian filter and various threshold values have been applied for preprocessing and edge following algorithm has been applied. Series of length data between edges have been generated from each image and compared using cross correlation coefficient. The result using cross correlation coefficient. The result using both edge following and cross correlation coefficient was proven to be the best fit for the proposed parts.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.202-204
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• 2004

An improvement of tracking capacity to find a position of the Iris images is presented in this paper. The propose algorithm is used the Four Points Diagonal Positioning algorithm that the image is positioned with arbitrary 4 points on the edge of iris and the selective 4 points are drawn by a diagonal line on the cross. The experiment result shows that the algorithm is efficient to track on the eyelid.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.24-27
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• 2004

An enhancement of tracking capacity to find a position of the Iris images is presented in this paper. The propose algorithm is called FFDP (Four Points Diagonal Positioning) that the image is positioned with arbitrary 4 points on the edge of iris and the selective 4 points are drawn by a diagonal line on the cross. The experiment result shows that the algorithm is efficient to track on the eyelid.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.100-111
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• 1999

This paper resents a discrete-time model of an edge-following with accommodation force control. Since an irregular workpiece shape causes disturbances to the system while following an edge, the use of preview control is proposed to improve the system performance. The preview control employs future information of the workpiece contour shape, and it can be developed by LQ-optimal control principles. This study provides a general method how to utilize the local future information obtained by the finite preview to minimize an optimality criterion evaluated over a problem duration. The force controller is designed based on the preview control scheme, and then implemented on a VME-based computer. Experimental results using an industrial robot show that the preview control system achieves faster tracking speed and better force regulation than the conventional nonpreview control system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1701-1704
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• 2005

We developed an machine vision method for navigation control of a traveling automatic guided vehicle(AGV) on desired trajectory with guided marks. The formulated EDF accumulates the edge magnitude for edge directions. The EDF has distinctive peak points at the vicinity of trajectory directions due to the directional and the positional continuities of desired trajectory. Examining the EDF by its shape parameters of the local maxima and symmetry axis results in identifying whether or not change in traveling direction of an AGV has occurred. Simulation results show that the presented method is useful for navigation control of AGV.