• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.125-130
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• 2013

In this paper, in order to overcome shortcomings of manual inspection for the automotive PWM Shaft, we developed an automated inline inspection system. The automated inline inspection system consists of the work feeder unit, conveying unit, outer diameter check unit, run-out and roundness check unit, machine vision, defective separation unit and status alarm unit. We used the machine vision system for automatic inspection process and designed the inline systems for automatic feeding and selecting process. Also the repeated operation test was performed in order to verify the precision and reliability of the proposed automated inline inspection system.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.184-191
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• 2004

In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.403-404
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• 2008

This report described the development of Vision Inspector program which can simulate numerically the image acquisition process of Machine Vision System for automatic optical inspection of any products. The program consists of an illuminator, a product to be inspected, and a camera with image sensor, and the final image obtained by ray tracing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1131-1135
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• 2005

Since human is vulnerable to emotional, physical and environmental distractions, most human inspectors cannot sustain a consistent 8-hour inspection in a day specifically for small components like door locking levers. As an alternative for human inspection, presented in this study is the development of a machine vision inspection system (MVIS) purposely for door locking levers. Comprises the development is the structure of the MVIS components, designed to meet the demands, features and specifications of door locking lever manufacturing companies in increasing their production throughput upon keeping the quality assured. This computer-based MVIS is designed to perform quality measures of detecting missing portions and defects like burr on every door locking lever. NI Vision Builder software for Automatic Inspection (AI) is found to be the optimum solution in configuring the needed quality measures. The proposed software has measurement techniques such as edge detecting and pattern-matching which are capable of gauging, detecting missing portion and checking alignment. Furthermore, this study exemplifies the incorporation of the optimized NI Builder inspection environment to the pre-inspection and post-inspection subsystems.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.112-116
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• 2007

If any of the set parameters such as the environment temperature, mold temperature are not maintained at a consistent level, the fail rate of injection molding products is increased. The price of the injection molding machine is very high, so in order to maximize the utilization of the machine that is required the production of a number of different products with minimum fail rate using a single machine. To prevent the defect products by an inspection process with perfect quality is very important to minimizing production of defect products in the molding process. Vision inspection systems are widely utilized in various manufacturing industries for quality assurance purposes. The vision inspection system consists of CCD camera and lighting system to capture the image of the subject of inspection, an image comparison algorithm using to determine the pass/fail of the products, and mechanical devices for the operation of the whole system. This research focuses on the development of the vision inspection system to process the inspection of an automobile parts. We developed a mechanical devices for the inspection of the injection molding products and an image comparison algorithm to determine the pass/fail result of the inspection based on the molding image and the accepted product image.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1030-1035
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• 2014

Machine vision inspection systems have replaced human inspectors in defect inspection fields for several decades. However, the inspection results of machine vision are often affected by small changes of illumination. When small changes of illumination appear in image histograms, the influence of illumination can be decreased by transformation of the histogram. In this paper, we propose an enhanced histogram matching algorithm which corrects distorted histograms by variations of illumination. We use the resolution resizing method for an optimal matching of input and reference histograms and reduction of quantization errors from the digitizing process. The proposed algorithm aims not only for improvement of the accuracy of defect detection, but also robustness against variations of illumination in machine vision inspection. The experimental results show that the proposed method maintains uniform inspection error rates under dramatic illumination changes whereas the conventional inspection method reveals inconsistent inspection results in the same illumination conditions.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.138-140
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• 2004

In this study, we develop a remocon inspection automatic system using machine vision technique. By our proposed inspection system, the inspection accuracy and processing time was considerably improved.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1072-1080
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• 2013

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.22-27
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• 2009

In this paper, an automatic functional inspection system EVT (Emulated Vision Tester) for LCD drive module PCB has been proposed and implemented. Typical automatic inspection system such as probing methods and vision-based systems are widely known and used, however, there exist undetectable defects due to critical timing factors which they may miss to catch from LCD equipments. Especially typical vision-based systems have inconsistency on acquisition of images so that distinction between gray scales can be difficult which results in low level of performance and reliability on the inspection results. The proposed EVT system is pure hardware solution. It directly compares pattern signals from a pattern generator to output signals from LCD drive module. It also inspects variety of analog signals such as voltage, resistance, wave forms and so forth. The EVT system not only shows high performance in terms of reliability and processing speed but reduces costs on inspection and maintenance. Also, full automation of entire production line can be realized when EVT is applied in in-line inspection processes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.177-180
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• 2002

Generally, it is very difficult to inspect geometric shape of large 2D objects after machining. To maintain the accuracy for inspection, a robot vision is used to divide overall shape into several enlarged images, and image processing technique is applied to acquire one minute geometric contour. The inspection is to compare the NC data with the measured contour data by the vision system, and the algorithm is to rotate to minimize the maximum deviation coinciding two geometric centers. This paper experimentally shows that the proposed inspection algorithm is very useful fur a large machined object.