• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.23-31
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• 2003

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.451-452
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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.391-392
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• 2007

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1106-1111
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• 2007

The visual inspection method that depends on human's eyes has some problem that a lot of variations happen in examination according to bodily, spiritual state of the checker. We automate remocon inspection process using CCD camera. Our developed inspection system can be used in any remocon production line without the user's big handling. Our inspection system was developed using PC, CCD Camera, Visual C++ for universal work place. The accuracy of proposed system was improved about 3.2[%] than the conventional pattern matching method and the processing time was decreased about 119[ms]. Also we showed that our inspection system is more robust to lighting circumstances.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.92-99
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• 2003

Quality inspection of textile products is an important problem for fabric manufacturers. This paper presents an automatic vision-based system for quality control of web textile fabrics. Typical web material is 1-3m wide and is driven with speeds ranging from 20m/min to 200m/min. At the present, the quality assessment procedures are performed manually by expert. But worker can not detect more than 60％ of the present defect and inspect the fabric if moving faster than 30m/min. To increase the overall quality and homogeneity of textile, an automated visual inspection system is needed fur the productivity. However, the existing inspection system are too expensive to purchase for small companies. In this paper, the proposed PC based real-time inspection algorithm gives low cost textile inspection system, high detection rate with good accuracy and low rate of false alarms. The method shows good results in the detection of several types of fabric defects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.472-478
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• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.145-152
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• 2004

This paper proposed efficient manufacturing system using the OMM (on-machine measurement) system. The OMM system is software based 3D modeler for inspection on machine and it is interfaced tool machine with RS232C. The software is composed of two inspection modules that one is touch probe operating module and the other is laser displacement sensor operating module. The module for touch probe has need of inspection feature that extracted it from CAD data. Touch probe moves to workpiece by three operating modes as follows: manual, general and automatic mode. The operating module of laser displacement sensor is used inspection for profile and very small hole. An Advantage of this inspection method is to be able to execute on-line inspection during machining or after it. The efficiency of proposed system which can predict and definite the machining errors of each process is verified, so the developed system is applied to inspect the mold-base(cavity, core).

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.405-406
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• 2010