• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1156-1161
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• 2006

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.856-862
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• 2020

Defect inspection system for industrial applications takes the important portion. Non-destructive inspection method has been significantly improved. Infrared thermography, as one of method for non-destructive inspection, can provide relatively precise data and quick inspection time. This study, it was performed to measure defect according to the measurement limit of the non-visible areas such as the back surface of the pipe using reflection plate using reflection plate based on Infrared thermography. The materials of the reflection plate were determined in consideration of the space limitation and the thermal characteristics, and defects were detected by the manufactured reflection plate. Detection of defect in non-visible area using the candidate materials for reflection plate was conducted.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.163-165
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• 2009

Automatic Vision Inspection(AVI) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer's specification in advance. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measuremet process. We only need are a simple experimental trial for repeated defect size measurement test. The statistical features from the experiement are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.906-908
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• 2009

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer's specification in advance. Also the prediction can indicate the level of current performance of an AVI system. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measurement process. For this purpose, only simple experiments are needed to measure the defect sizes for certain number of times. The statistical features from the experiment are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.2004-2011
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• 2004

The applicability of the ultrasonic C-scan inspection is restricted due to the deterioration of mechanical properties of specimen during the test. Therefore, the aim of this research is applied to Eddy Current (EC) test substitute for the C-scan inspection in CFRP tube containing defects. This research is to evaluate the EC signals for the inspection of CFRP tube containing various circular hole defects (20% to 100% depth to the specimen thickness) using the unloading specimen and radial loading specimen. This study was considered the following points; 1) Analysis of EC signals for the inspection of saw-cut defect and circular hole defect, 2) The evaluation of defect depths and EC signals relationship. 3) Variation of EC signal owing to the radial load. In conclusions, the high frequency such as 300∼500 kHz made it possible to the inspection of 40% to 100% defects. Particularly, in case of 20% defect, the EC signal was not detected due to the noise of micro-crack and delamination. While the depth of the hole defects were decreasing, the difference of the phase angle between unloading specimen and radial loading specimen was gradually increasing.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.499-506
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• 2004

The copper foil surface inspection system is necessary for the factory automation and product quality. The developed system is composed of the high speed line scan camera, the image capture board and the processing computer. For the system resource utilization and real-time processing, multi-threaded architecture is introduced. There are one image capture thread, 2 or more defect detection threads, and one defect communication thread. To process the high-speed input image data, the I/O overlap is used through the double buffering. The defect is first detected by the predetermined threshold. To cope with the light irregularity, the compensation process is applied. After defect detection, defect type is classified with the defect width, eigenvalue ratio of the defect covariance matrix and gray level of defect. In experiment, for high-speed input image data, real-time processing is possible with multi -threaded architecture, and the 89.4% of the total 141 defects correctly classified.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1079-1082
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• 2005

This paper deals with the algorithm development that inspects defects such as Lens Focus, Focus check, Black Defect, Dark Defect, Dim Defect, Color Defect, and Line Defect, Angle Defect, IrisAgc Defect caused by the process of 2M Class Compact Camera Module (CCM). Domestic market was majorly comprised of VGA(0.3 million pixel) market. But in the middle of year 2004, camera phone with Mega Pixel has appeared, and it is estimated that the camera phone with Mega Pixel will take up to 28% of total phone sales if it is released in the end of year 2004. Since the inspection of finished products is done manually, it is major obstacle in production increment In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of assembled CCM. The performances of the developed inspection system and we can recognize various types of defect of CCM modules with good accuracy and high speed

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.432-435
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• 2005

The Mega-pixel camera phones become main trends in mobile phone market. The lens modules used in mesa-pixel camera phones need high resolution. One of the main factors of resolution drop is the defects of bare lens. Though there are many advantages in auto-inspection of defects of bare lens, high technical problems take the defect inspections to be done with manual process. In this paper, the type and the source of defects were described and bare lens defect auto-inspection system design was explained. The designed auto-inspection system is composed of illumination optics part, focusing optics part and auto-moving system. With the proposed auto-inspection system, fast and uniform inspection of bare lens can be achieved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.831-832
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.7-14
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• 2007