• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.135-137
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• 2004

In this study we'll deal with the small-sized metalized film capacitors with large capacity which head have $5mm{\times}5mm{\times}2.5mm$ dimension. The lead wire is used to weld at both sides of capacitors. At that time the position gap between the welding machine and lead wire supplier would cause the welding error. Also, during the tapping processing of metalized film capacitors, the interval error among the capacitors, the length error of lead frame attached at the capacitors, and the straightness distortion of the lead frame could happen. As mentioned, four kinds of error parameters will be measured and analyzed by using the automatic visual inspection system that is implemented with CCD camera, optical parts, background lighting, and image processing algorithms. Finally we are able to achieve success rate above 99% to detect the welding faults of capacitors in the field test.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.66-78
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• 2001

This paper deals with problem of determining process target value under automated visual inspection(AVI) system. Three independent error sources - digitizing error, illumination error, and positional error - which have a close relationship with the performance of the AVI system, are considered. Assuming that digitizing error is uniformly or normally distributed and illumination and positional errors are normally distributed, respectively, the distribution function for the error of measured lengths is derived when the length of a product is measured by the AVI system. Then, Optimal target values under two error models of AVI system are obtained by minimizing the total expected cost function which consists of give away, rework and penalty cost. To validate two process setting models, AVI system for drinks filling process is made up and test results are discussed.

• International Journal of Quality Innovation
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• v.7 no.3
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• pp.58-69
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• 2006

This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.335-338
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• 2004

In this study has developed analysis system for automatic inspection of FPD(Flat Panel Display) characteristic, such as brightness, view angle, color ratio in the manufacturing process. Developed system consists of inspection-sensor part, acquiring a data by 3-CCD Color CCD camera and Inspection-stage part, driving a FPD holder to rotation and tilt direction. In experiment results, we could have ensured easily brightness distribution, available view angle, color reproduce and could expect to improve the quality, productivity, and yield.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.202-209
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• 2004

Quality control is essential to the final product in BGA-type PCB fabrication. So, many automatic vision systems have been developed to achieve speedy, low cost and high quality inspection. A multiple threshold selection algorithm is a very important technique for machine vision based inspection. In this paper, an inspected image is modeled by using fuzzy sets and then the parameters of specified membership functions are estimated to be in maximum fuzzy entropy with the probability of the fuzzy sets, using the exhausted search method. Fuzzy c-partitions with the estimated parameters are automatically generated, and then multiple thresholds are selected as the crossover points of the fuzzy sets that form the estimated fuzzy partitions. Several experiments related to flip chip BGA images show that the proposed algorithm outperforms previous ones using both entropy and variance, and also can be successfully applied to AVI systems.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.16-21
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• 2015

In this paper, we presented Under Vehicle Inspection System by comparing two image signals. Two signals are generated by license plate number and under-vehicle pattern recognition. The test shows reliable precision within real-time of 2.8sec, which can be applicable commercially. In the future, more research will be conducted to enhance the precision by automatic image balance in many challenging situations.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.422-424
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• 2006

This paper suggests an automatic spot-inspection algorithm for LCD modules. Usually, LCD module testing is classified by two categories. One is for uniform pattern testing and the other is Non-uniform testing. The uniform pattern testing is well defined and also fully automated in the factory. However non-uniform pattern testing is not defined well yet, so non-uniform testing is conducted by human operators. In this paper a spot-pattern, which is one of non-uniform pattern, inspection algorithms are proposed. The performance of the proposed algorithm is tested by extensive simulations using artificial slot-patterns and real ones in the LCD modules.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.117-120
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• 1996

In this paper, a new approach to acquire the cross-sentional image for automatic solder joint inspection of double-sided PCB using X-ray source is presented. We designed the apparatus with fixed X-ray source to realize the cross-sectional image by tunning object and detector synchronously. The cross-sectional images are captured at several view angle of X-ray source, the geometric image distortions caused by view angle and the shape of image intensifier are compensated. The precision variation of cross-sectional image by the change of view angle was investigated. Also we acquired the cross-sectional image to the solder joint of double-sided PCB and reconstructed the shape of solder joint.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.105-109
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• 2001

The micro optical parts such as ferrules are required to be manufactured within very small tolerances, as the slight deviation of the tolerance would give very large amount of loss in communication efficiency. For efficient optical communication, outer diameter, fiber diameter, fiber separation and eccentricity are significant parameters to be inspected., Thus we developed an automatic inspection system to evaluate shape parameters of the optical fiber connectors(ferrule) upto submicron accuracy using machine vision. new optical probe of multi fields of views has been developed and the image processing and data analysis algorithms have been complemented in real time basis. The developed system is successfully used in the practical ferrule manufacturing industry, and about 0.1$\mu\textrm{m}$ accuracy can be obtained with very fast inspection time.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.131-136
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• 2001

The purpose of this paper is to develop image inspection system endows an automatic operating and measuring that the moment values are invariant with respect to variable object size and rotation. In this paper, using these moment feature vector with Hu s 7 invariant moment is also given. The characteristics of section which is applied in the mechanics used moment descriptor of invariant moment detection algorithm for image inspection system. Corresponding rates between 94% and 96% have been achived for all object tested.