• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.49-58
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• 2014

This paper proposes a new assessment and reliability validation method of Lane Departure Assistance System based on DGPS-GIS by measuring lanes with camera vision. Assessment of lane departure is performed with yaw speed measurement and determination method for false alarm of ISO 17361 and performance validation is executed after generating departure warning boundary line by considering deviation error of LDAS using DGPS. Distance between the wheel and the lane is obtained through line abstraction using Hough transformation of the lane image with camera vision. Evaluation validation is obtained by comparing this value with the distance obtained with LDAS. The experimental result shows that the error of the extracted distance of the LDAS is within 5 cm. Also it proves performance of LDAS based on DGPS-GIS and assures effectiveness of the proposed validation method for system reliability using camera vision.

• Journal of Welding and Joining
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• v.19 no.2
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• pp.200-207
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• 2001

Three-diemnsional bead profile was measured using the biprism stereo vision sensor in GMAW, which consists of an optical filter, biprism and CCD camera. Since single CCD camera is used, this system has various advantages over the conventional stereo vision system using two cameras such as finding the corresponding points along the horizontal scanline. In this wort, the biprism stereo vision sensor was designed for the GMAW, and the linear calibration method was proposed to determine the prism and camera parameters. Image processing techniques were employed to find the corresponding point along the pool boundary. The ism-intensity contour corresponding to the pool boundary was found in the pixel order and the filter-based matching algorithm was used to refine the corresponding points in the subpixel order. Predicted bead dimensions were in broad agreements with the measured results under the conditions of spray mode and humping bead.

• Journal of Ocean Engineering and Technology
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• v.24 no.4
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• pp.72-77
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• 2010

This paper presents a method for measuring the shaft power of a marine main engine. Usually, in traditional systems for measuring shaft power, a strain gauge is used even though it has several disadvantages. First, it is difficult to set up the strain gauge on the shaft and acquire the correct signal for analysis. Second, it is very expensive and complicated. For these reasons, we investigated alternative approaches for measuring shaft power and proposed a new method that uses a vision-based measurement system. For this study, templates for image processing and CCD cameras were installed at the both ends of the shaft. Then, in order for the cameras to capture the images synchronously, we used a trigger mark and a optical sensor. The position of each template between the first and the second camera images were compared to calculate the torsion angle. The proposed measurement system can be installed more easily than traditional measurement systems and is suitable for any shaft because it does not contact the shaft. With this approach, it is possible to measure the shaft power while a ship is operating.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.71-78
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• 2020

This paper proposes vision sensors and deep learning-based around view monitoring system for ship berthing. Ship berthing to the port requires precise relative position and relative speed information between the mooring facility and the ship. For ships of Handysize or higher, the vesselships must be docked with the help of pilots and tugboats. In the case of ships handling dangerous cargo, tug boats push the ship and dock it in the port, using the distance and velocity information receiving from the berthing aid system (BAS). However, the existing BAS is very expensive and there is a limit on the size of the vessel that can be measured. Also, there is a limitation that it is difficult to measure distance and speed when there are obstacles near the port. This paper proposes a relative distance and speed estimation system that can be used as a ship berthing assist system. The proposed system is verified by comparing the performance with the existing laser-based distance and speed measurement system through the field tests at the actual port.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.61-70
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• 2001

This paper introduces a new digitization method with sensor fusion for shape measurement in reverse engineering. Digitization can be classified into contact and non-contact type according to the measurement devices. Important thing in digitization is speed and accuracy. The former is excellent in speed and the latter is good for accuracy. Sensor fusion in digitization intends to incorporate the merits of both types so that the system can be automatized. Firstly, non-contact sensor with vision system acquires coarse 3D point data rapidly. This process is needed to identify and loco]ice the object located at unknown position on the table. Secondly, accurate 3D point data can be automatically obtained using scanning probe based on the previously measured coarse 3D point data. In the research, a great number of measuring points of equi-distance were instructed along the line acquired by the vision system. Finally, the digitized 3D point data are approximated to the rational B-spline surface equation, and the free-formed surface information can be transferred to a commercial CAD/CAM system via IGES translation in order to machine the modeled geometric shape.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.49-56
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• 2014

Generally, the tool presetter is utilized to align and measure some specific dimensions of a machine tool. It is classified into two types(contact and contactless) according to the measurement method, and the optical sensor based contactless scheme has the advantages of measurement flexibility and convenience. This paper describes the design and realization of an industrial tool presetter using machine vision and linear scaler. Before measurement, the objective tool is attached to the mechanical mount and is aligned with the optical apparatus. After capturing tool images, the suggested image processing algorithm calculates its dimesions accurately, combining the traversing distance from the linear scaler. Experimental results conforms that the present tool presetter system has the precision within ${\pm}20um$ error.

• 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 Korean Society for Precision Engineering
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• v.15 no.12
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• pp.7-13
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• 1998

In this paper, an automatic ball-stud inspection system has been developed using the computer-aided vision system. Index table has been used to get the rapid measurement and multi-camera has been used to get the high resolution in physical system. Camera calibration was suggested to perform the reliable inspection. Image processing and data analysis algorithms for ball stud inspection system have been investigated and were performed quickly with high accuracy. As a result, inspection system of a ball stud could be used with a high resolution in real time.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5854-5860
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• 2014

The on-site performance of a vision-based displacement measurement system (VDMS) was evaluated through a field test on a bridge. The VDMS used in this study is composed of a camera, a marker, a frame grabber, and a laptop. The system measures the displacement by attaching a marker at the location to be measured on the structure, by capturing images of that marker with a fixed rate, and by processing a series of images using a planar homography technique. The developed system was first validated from a laboratory test using a small-scale building structure. The VDMS was then employed in a field test on a railroad bridge with a KTX train running under various conditions. The on-site performance was evaluated by comparing the obtained displacement using the VDMS with the displacement measured from a laser Doppler vibrometer (LDV), which is an expensive and accurate displacement measurement device.