• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.125-130
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• 2016

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.62-75
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• 2008

Vision-based simultaneous localization and map building using a single camera, while compelling in theory, have not until recently been considered extensive in the practical realm of the real world. In this paper, we propose a simple framework for the monocular SLAM of an indoor mobile robot using natural line features. Our focus in this paper is on presenting a novel approach for modeling the landmark before integration in monocular SLAM. We also discuss data association improvement in a particle filter approach by using the feature management scheme. In addition, we take constraints between features in the environment into account for reducing estimated errors and thereby improve performance. Our experimental results demonstrate the feasibility of the proposed SLAM algorithm in real-time.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.301-306
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• 2016

This paper presents the results of a study for robust self-localization and indoor slam using external cameras (such as a CCTV) and odometry of mobile robot. First, a position of mobile robot was estimated by using maker and odometry. This data was then fused with camera data and odometry data using an extended kalman filter. Finally, indoor slam was realized by applying the proposed method. This was demonstrated in the actual experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.548-554
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• 2009

We propose an automatic inspection system for hologram with multiple patterns. The system hardware consists of illuminations, camera, and vision processor. Multiple illuminations using LEDs are arranged in different directions to acquire each image of patterns. The system software consists of pre-processing, pattern generation, and pattern matching. The acquired images of input hologram are compared with their reference patterns by developed matching algorithm. To compensate for the positioning error of input hologram, reference patterns of hologram for different position should be generated in on-line. We apply a frequency transformation based CGH(computer-generated hologram) method to generate reference images. For the fast pattern matching, we also apply the matching method in the frequency domain. Experimental results for hologram of Korean currency are then presented to verify the usefulness of proposed system.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.281-290
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• 2015

Human action recognition from a video scene has remained a challenging problem in the area of computer vision and pattern recognition. The development of the low-cost RGB depth camera (RGB-D) allows new opportunities to solve the problem of human action recognition. In this paper, we present a comprehensive review of recent approaches to human action recognition based on depth maps, skeleton joints, and other hybrid approaches. In particular, we focus on the advantages and limitations of the existing approaches and on future directions.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.120-129
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• 2003

For successful establishment of the roughing CAM system based on reverse engineering, it is necessary to develop the measurement method for generation of roughing path from a physical footwear model. In this study, the development of the roughing path measurement system is presented. It consists of 3 CCD cameras, image acquisition board and the roughing path measurement algorithm. The 3 CCD cameras capture images of the sidewall and the bottom of the footwear and, from two images, the outer and inner lines are extracted using image-processing algorithm. The roughing path measurement algorithm generates the roughing path which is reflected on the change of resolution according to the distance between the CCD camera and the measured point. The experimental results show that the developed system can measure the roughing path within the allowable roughing error range.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3101-3104
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• 1999

It is important to detect objects movement for obstacle recognition and path searching of autonomous robots and vehicles with vision sensor. This paper shows the method to draw out objects and to trace the trajectory of the moving object using a CCD camera and it describes the method to recognize the shape of objects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.149-153
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• 2004

A Impulse denosing filter design of image for the faster processing time and system compatibility using DSP processor is presented on this paper The system hardware is composed of the stand-alone board with 32 bits DSP processor and vision board for image data acquisition with NTSC CCD camera, and the host computer controls them. The denoising method uses the adaptive median filter. The experiment result is that the system leads to denosing effect as 90% and PSNR 22㏈

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.309-314
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• 1999

The major movement block of the containers is range between apron and designation points on yard in container terminal. The yard tractor operated by human takes charge of it's movement in conventional container terminal. In unmanned container terminal, UCT(unmanned container transporter) has charge of the yard tractor's role and the navigation path is ordered from upper level control system. The unmanned container terminal facilities must have docking system that guided landing line to have high speed travelling and precision positioning in unmanned container terminal. The general method for docking uses the vision system with CCD camera, infra red, and laser. This paper describes the investigation for the developed docking method in view point of merit and demerit and introduces 속 result of developing the docking system with LSB(laser slit beam).

• Journal of Power System Engineering
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• v.6 no.1
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.