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Lee, Yong-Joong
- Transactions of the Korean Society of Machine Tool Engineers
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- v.13 no.3
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- pp.37-43
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- 2004
The purpose of this study is to develop a practical image inspection system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from $30^{\circ}$ to $45^{\circ}$ simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment, the image inspection system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94% to 96%. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automation when the image inspection system developed from this research is applied to the productive field.
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Baik, Seung-Yeb
- Journal of the Korean Society of Manufacturing Technology Engineers
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- v.20 no.5
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- pp.666-672
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- 2011
In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.
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이문규;김채수
- 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.
https://doi.org/10.5302/J.ICROS.2003.9.2.152 인용 PDF KSCI

Kim, Hyung-Kuk;Ahn, Hee-Tae;Lee, Dong-Hwal;Jeong, Seung-Gwon;Bae, Jong-Il
- 제어로봇시스템학회:학술대회논문집
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- 2001.10a
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- pp.127.5-127
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- 2001
The 3-dimensional measuring machine by using an ultrasonic sensor is used one of the NDE (Nondestructive Evaluation). It is applied to the inspection of pipelines, boreholes, pressure vessel and tank, and so on. On particular when a harsh environment prohibits the use of moving mechanical parts. The 3-dimensional measuring machine by using an ultrasonic sensor, which measure 1-dimensional information and 2-dimensional information simultaneously from a target of inspection, and then re construct 3-dimensional information. So we can find the situation in progress and predict remaining life and corrosion without destructive examination. It´s a point of excellence that the 3-dimensional measuring machine is portable.
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이동목;이광일;양승한
- 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.
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