• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.370-376
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• 2016

Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.397-408
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• 2009

Image training is a very important yet difficult state for automated visual inspection using computers. Because the size of parts for the recently produced PCB (Printed Circuit Board) becomes smaller and circuit patterns gradually become more complex, a difficult and complex training process is becoming a big problem within an industry where development cycle for new products is short and various products must be inspected. This research produced a reference image by using CAD (Gerber) file which becomes a standard for PCB automatic visual inspection. Reference image from a Gerber file guarantees PCB patterns with no defects. Through system implementation and experimentation, Gerber file is used in order to propose a plan which allows an easy training process for PCB automatic visual inspection system.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.305-310
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• 2003

In this paper we deal with the system design and development of the high-speed automatic precision inspection for the defects of bolts. In order to inspect bolts continuously, we used the conveyor system. Also, this conveyor includes the servo motor and encoder to achieve accurate movement. According to encoder signal, line-scan camera captures the line-by-line image of bolts and after one frame is accumulated, various parameters are calculated and inspected by image processing algorithms. Experimental results using the developed facilities are presented to demonstrate the efficiency of the proposed equipment.

• IE interfaces
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• v.10 no.3
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• pp.133-143
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• 1997

In this paper, an improved method is developed for automatic inspection system using simbology patterns. The developed method uses the two previously developed matching methods the template maching method and the feature matching method. The template matching method is very sensitive to variations of target images such as translation and rotation of objects. On the other hand, the feature matching method doesn't extract proper features in some types of symbology patterns. The proposed method shows the improvement of precision in recognition of defects and flexibility of different types of symbology patterns.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.55-60
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• 2008

Inspection of steel columns which is one of the most critical elements in construction requires trained surveyor(s). Also it takes time to handle survey device(s) delicately for accurate measurements. To improve the inspection process of steel columns, the previous studies developed the AR prototype system, ARCam, and showed that ARCam is a promising inspection device that can reduce inspection time. However, ARCam still requires a surveyor to make measurements based on his visual perception and judgment This study proposes an algorithm for automatic inspection based on ARCam. The algorithm is based on image processing and computer vision and focuses on the inspection of steel column plumbness. This method will make measurements without a surveyor's judgment. The ultimate purpose of the automatic inspection is to minimize the surveying labor, thus reducing inspection time and cost.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1559-1564
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• 2011

This study presents the development of a machine vision inspection system(MVIS) purposely for car seat frames as an alternative for human inspection. The proposed MVIS is designed to meet the demands, features and specifications of car seat frame manufacturing companies in striving for increased throughput of better quality. This computer-based MVIS is designed to perform quality measures by detecting holes, nuts and welding spots on every car seat frame in real time. In this study, the NI Vision Builder software for Automatic Inspection was used as a solution in configuring the aimed quality measurements. The techniques for visual inspection are optimized through qualitative analysis and simulation of human tolerance on inspecting car seat frames. Furthermore, this study exemplifies the incorporation of the optimized vision inspection environment to the pre-inspection and post-inspection subsystems. The system built on this proposed MVIS for car seat frames has successfully found the possible detections.

• IE interfaces
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• v.4 no.2
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• pp.43-51
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• 1991

A line search method is developed to locate all the conerpoints of 2-dimensional polygon images for inspection purposes. This optimization-based method is used to approximate a 2-D curved object by a polygon. This scheme is also developed for inspection of objects in industrial environment. The inspection 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.118-121
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• 2002

In this study, we describe the development of viscous inspection equipment for flatron panel glass by Moire phenomenon and propose a new idea to develop an automatic inspection system for viscous or cord defects. It is possible to detect string viscous more easily and the equipment is practically being applied in production line. After using this equipment, the ratio of defective from customer is dropped significantly.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.16-25
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• 2008

The micro needle means the ultrafine probe of 'Probe Card'. The size of micro needle is so minute that it is difficult to minute that it is difficult to inspect it with eyes. On the other hand it is very critical if there is a defect in micro needle of probe card. In this study, we developed an automatic visual inspection system for finding defect status in probe angle, tip length and diameter. Through the experimental results, we could find that our proposed method is better than human-eyes inspection method in accuracy and inspection speed, and also in robustness to lighting circumstances.