• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.821-822
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• 2010

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.91-97
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• 2012

The automated visual inspection system (machine vision system) for quality assurance is an important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. The world market of the machine vision components is expected 18 billon dollars in 2015. Therefore, there is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we propose a technical training program for the machine vision technology. The total time of training is 30 to 60 hours and the training program can operate flexibly by student's major, a priori knowledge and education level.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.409-415
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• 2022

In computer vision, an image of a measurement target is acquired using a camera. And feature values, vectors, and regions are detected by applying algorithms and library functions. The detected data is calculated and analyzed in various forms depending on the purpose of use. Computer vision is being used in various places, especially in the field of automatically recognizing automobile parts or measuring the quality. Computer vision is being used as the term machine vision in the industrial field, and it is connected with artificial intelligence to judge product quality or predict results. In this study, a vision system for judging the quality of automobile parts was built, and the results were compared by applying five machine learning classification models to the produced data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.517-518
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• 2008

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.6
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• pp.22-29
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• 2022

In this study, an automatic marking system for fabric inspection machines was developed. The main objectives of the study were to promote intelligence and automation for the inspection process, as well as to increase textile industrial productivity. Generally, when a worker manually inspects and marks a fabric, human error and reduced efficiency are unavoidable. To overcome these problems, we developed an automatic marking system that uses robots. This system incorporates a vision camera to automatically recognize defects, and an optical fiber sensor to detect the side of the fabric. To verify the performance, the control system sends a command directly to the robot to mark the fabric. Finally, the actual production confirmed that the proposed system could perform the desired motion.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.58-63
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• 2009

The appearance inspection of various electronic products and parts was executed by the eyesight of human. The appearance inspection is applied to the most electronic component of LCD Panel, flexible PCB and remote control. If the appearance of electronic products of small and minute size is inspected by the eyesight of human, we can't expect the stable inspection result because inspection result is changed by condition of physical and spirit of the checker. Therefore currently machine vision systems are used to many appearance inspection fields instead of inspection by human. The many problems of inspection by the checker are not occurred in machine vision circumstance. However, the inspection by automatic machine vision system is mainly influenced by illumination of workplace. In this paper, we propose a histogram transform method for improving accuracy of machine visual inspection.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.150-155
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• 2013

This work present a new method of sealing inspection system for vehicle in which foam rubber materials are used for sealing the vehicle parts. This system is composed from a devices comprising non-contact and real-time scanning on visual inspection in machine parts. We have been investigated qualitative factors that influenced on sealing system of vehicle structure which flexibly attenuated vibration and plenty of foam rubber materials having elastic property. However, there are different factors which still depended on outdated technique (personnel subjective judgment) in the performance inspection of rubber parts, specially for cross section inspection. Through a newly developed inspection system which recently applied for the production line, we successfully achieved more effective results of matching rate by about 80 % in the sealing performance inspection with 0.7% to 1.4% in the repeated errors. These are resulted from non-contacted response by CCD camera and vision program using geometry matching method. We expect that this system may be widely applied in the strict inspection parts of more diverse cross-section in future.

• Journal of Korean Society for Quality Management
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• v.32 no.1
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• pp.63-74
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• 2004

Recently, enterprises have focused on quality improvement for delighting their customers. Especially, all business sector have checked, analyzed their consumer complaints in detail on their products and made a plan to reduce them. But there is a limitation not to solve them. This paper presents one of tools to reduce non qualified product on their operation line directly by modernized IT technology after analyzing and making the plan.

• 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.