• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.75-80
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• 2008

This paper presents a vision based autonomous inspection system for welding quality control of a RV sinking seat. In order to overcome the precision error that arises from a visible inspection by an operator in the manufacturing process of a RV sinking seat, the machine vision based welding quality control system is proposed. It consists of the CMOS camera and the NI vision system. The geometry of the welding bead, which is the welding quality criteria, is measured by using the captured image with a median filter applied on it. The image processing software for the system was developed using the NI LabVIEW software. The proposed welding quality inspection system for RV sinking seat was verified using experimentation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.71-77
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• 2008

This paper presents a stereo vision based autonomous inspection system for welding quality control of a RV(Recreational Vehicle) sinking seat. The three dimensional geometry of the welding bead, which is the welding quality criteria, is measured by using the captured stereo images with a median filter applied on it. The image processing software for the system was developed using the NI LabVTEW software with NI vision system. In the manufacturing process of a RV sinking seat, the developed system can be used for overcoming the precision error that arises from a visible inspection by an operator. The welding quality inspection system for RV sinking seat was verified using experimentation.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.59-63
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• 2010

This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.309-310
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• 2006

This paper is about the development of surface inspection of bearing inner and outer race using machine vision. Before this system is developed, most inspections are performed by workers' naked eye. To improve both the inconvenience and incorrectness, another new tester is introduced. This system has the three sections mainly. First one is the mechanism section which transfers bearing manufactured from previous process line to the testing process in plant. Another is the inspection system which is composed of two parts: computer vision and measurement system using laser diode which inspects the defects of the bearing inner or outer race. The other is the pneumatic cylinder part controlled by Programmable Logic Controller(PLC). The system which is developed shows favorable results, and that has the advantage of convenience and correctness compared to previous system.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.152-158
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• 2003

A machine-vision guided inspection system with go-no gauges for inspecting eggcrate assemblies in steam generators is considered. To locate the gauge at the right place, periodic corrective actions for its position and traveling direction are required. We present a machine vision algorithm for determining inserting position and traveling direction of the go-no gauge. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid-height adjustment, intersection point estimation between two intersecting grids, and adjustment of position and traveling direction of the gauge. The intersection point estimation is performed by using linear regression with a constraint. A test with a real eggcrate specimen shows the feasibility of the algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.245-250
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• 2003

Today, automobile world market is highly competitive. In order to strengthen the competitiveness, quality of automobile is recognized as important and efforts are being made to improve the quality of manufactured components. The directional ability of automobile has influenced on driver directly and hence it must be solved on the preferential basis. In the present research an automated vision system has been developed th inspect the front chassis module. To interpret the inspection data obtained for front chassis module, new interpreting algorithm have been developed. Previously the control of tolerance front chassis module was done manually. With the help of the new algorithm developed, the dimension is calculated automatically to check whether the front chassis module is within the tolerance limit or not.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.795-801
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• 1998

In this paper, we propose a machine vision algorithm for inspecting inserts which are used for milling and turning operations. Major defects of the inserts are breakage and crack on insert surfaces. Among the defects, breakages on the face of the inserts can be detected through three stages of the algorithm developed in this paper. In the first stage, a multi-layer perceptron is used to recognize the inserts being inspected. Edge detection of the insert image is performed in the second stage. Finally, in the third stage breakages on the insert face are identified using Hough transform. The overall algorithm is tested on real specimens and the results show that the algorithm works fairly well.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.397-406
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• 1998

The purpose of this research is to develop an integrated quality inspection system using machine vision technology in the automotive engine assembly process. The system makes it possible for the inspected data to be entered directly from the machine vision system into the developed system without the need for intermediate operations. Such direct entry enables prompt corrective actions against process problems. An IVP-150 machine vision board is installed an the PC for image processing, and a template matching technology is implemented to precisely verify quality factors. The developed system is successfully installed in a manufacturing process, and it showed robustness to the problems of noise, distortion, and orientation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.399-400
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.401-402
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• 2007