• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.261-268
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• 2014

Precision screws have a wide range of industrial applications such as electrical and automotive products. To produce screw threads with high precision, not only high precision manufacturing technology but also reliable measurement technology is required. Machine vision systems have been used in the automatic inspection of screw threads based on backlight illumination, which cannot detect defects on the thread surface. Recently, an omnidirectional inspection system for screw threads was developed to obtain $360^{\circ}$ images of screws, based on front light illumination. In this study, the illumination design for the omnidirectional inspection system was modified by adding a light shield to improve the image uniformity. Optical simulation for various shield designs was performed to analyze image uniformity of the obtained images. The simulation results were analyzed statistically using response surface method, from which optical performance of the omnidirectional inspection system could be optimized in terms of image quality and uniformity.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.3
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• pp.8-14
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• 2011

The clogging of the flow area at the tube support plates(TSPs), especially at the upper TSPs results in the water level oscillation of a steam generator during normal operation. A reduction of the TSP flow area causes to increase in pressure drop within the two-phase flow zone, which destabilizes the boiling flow through the tube bundle. This phenomenon was occasionally observed at a few domestic and foreign nuclear power plants. One of the methods for defining the flow area clogging is visual inspection, which is the most effective inspection method. The results of the visual inspection for TSPs' flow area are clogging images on TSPs' quartrefoil lobes. These images are complexly distorted due to lens aberration and external factors like the distance to a subject and angle etc. In this work, we developed the analysis algorithm for clogging image of the TSP flow area of steam generators. For this purpose, we designed an image verification device applicable to the camera employed in the field for visual inspection and then, we demonstrated the validity of image analysis algorithm by using this device and commercial autoCAD program.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.140.2-140
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• 2001

In this paper, we develop the system which inspects the metal mask using area scan camera and belu type xy-table and introduce its inspection algorithm. Thes whole area of the metal mask is divides into several inspection block and the sixe of a inspection block is decided by FOV(Field of View). To compare with the camera image of each block, the reference image is made by gerber file. The ratation angle of the metal mask is calculated through the linear equation that is substituted two end points of horizontal boundary of a specific hole in a camera image for. To calculate the position error caused by belt type xy-table, hough-transform using the distances among the holes in two images os used. The center of the reference image is moved as much as the calculated position error to be coincide with the camera image ...

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.184-191
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• 2004

In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.561-562
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• 2009

The needs for inspection automation for more systematic and efficient maintenance were gradually increased by several inspectors and researchers. With the robotic and digital image processing technologies, in this paper, new inspection automation system were introduced and tested in the real PSC box crack inspection procedures The configuration and scheme of robotic inspection and digital image processing algorithms were represented. The designed robotic sensors and image processing system were tested and the feasibility and possibility of the robot based automatic inspection were approved in the real PSC box bridges.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.82-87
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• 1998

Laser printer, faximile and copy machine are a few examples of OA(office automation) system. In such a system, the reflecting mirror has been employed for transmitting a target image to optical device. Therefore, to develope a good quality of optical system, the quality control of optical mirror was required. In recent years, considerable efforts have been directed toward the development of automated optical glass inspection system because the inspection is eye-fatigue and monotonous job for humans to perform. In this paper, we propose a inspection system applying algorithm of image processing for detecting defects of optical glass such as pinhole, scratch. From the experiments, the proposed inspection system shows reliable results.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.444-452
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• 2008

This paper presents an overall image processing approach of defect inspection of patterned TFT-LCD panels for the real manufacturing process. A prototype of AOI(Automatic Optical Inspection) system which is composed of air floating stage and multi line scan cameras is developed. Adjacent pattern comparison algorithm is enhanced and used for pattern elimination to extract defects in the patterned image of TFT-LCD panels. New region merging algorithm which is based on border expansion is proposed to identify defects from the pattern eliminated defect image. Experimental results show that a developed AOI system has acceptable performance and the proposed algorithm reduces environmental effects and processing time effectively for applying to the real manufacturing process.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.171-171
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• 2000

We have developed m innovative surface inspection system for automated quality control for steel products in POSCO. We had ever installed the various kinds of surface inspection systems, such as a linear CCD and a laser typed surface inspection systems at cold rolled strips production lines. But, these systems cannot fulfill the sufficient detection and classification rate, and real time processing performance. In order to increase detection and classification rate, we have used the Dark, Bright and Transition Field illumination and area type CCD camera, and fur the real time image processing, parallel computing has been used. In this paper, we introduced the automatic surface inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms and its performance obtained at the production line.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.32-40
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• 2003

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1508-1515
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• 2017

This paper proposes the defect detection method for automatic inspection machines in printed circuit boards (PCBs) manufacturing system. The defects of PCB such as open, short, pin hole and scratch can be detected by comparing the standard image and the target image. The standard image is obtained from CAD file such as ODB++ format, and the target image is obtained by arranging, filtering and binarization of captured PCB image. Since the PCB size is too large and image resolution is too high, the image processing requires a lot of memory and computational time. The wavelet transform is applied to compress the standard and target images, which results in reducing the memory and computational time. To increase the inspection accuracy, we utilize the he HH-domain as well as LL-domain of the transformed images. Experimental results are finally presented to show the performance improvement of the proposed method.