• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.381-382
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• 2015

Small devices such as MLCC, sample inspection on the processing is not easy. If you can proceed with the sample inspection, the production process will be able to maximize the MLCC production efficiency. In this study, to minimize the interference of operator, and to maximize the operating efficiency of the equipment. Use image processing techniques for its extracts the position and angle of the MLCC. Implements an automatic inspection system with the high productivity.It is possible to inspect the final six MLCC devices. And once we Pick-Up to 200 Chip to check the accuracy of 98.4%. Based on the results of various studies are in progress to be expected to be applicable to the automatic inspection equipment side development of a variety of small devices.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.276-282
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• 2015

This paper proposes a SMD (surface mounting device) classification method for the PCB assembly inspection machines. The package types of SMD components should be classified to create the job program of the inspection machine. In order to reduce the creation time of job program, we developed the automatic classification algorithm for the SMD packages. We identified the chip-type packages by color and edge distribution of the images. The input images are transformed into the HSI color model, and the binarized histroms are extracted for H and S spaces. Also the edges are extracted from the binarized image, and quantized histograms are obtained for horizontal and vertical direction. The neural network is then applied to classify the package types from the histogram inputs. The experimental results are presented to verify the usefulness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.448-455
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• 2003

A system design technique of automatic thickness measurement and defect inspection system, which measures the thickness of the ALC(Autoclaved Lightweight Concrete) block and inspects the defect on a realtime basis is proposed. The image processing system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. The image obtained by this system was analyzed by a devised algorithm, specially designed for the enhanced measurement accuracy. For the realization of the proposed algorithm, the preprocessing method that can be applied to overcome uneven lighting environment, an enhanced edge decision method using 8 edge-pairs with irregular and rough surface, the unit length decision method in uneven condition with rocking objects, and the curvature calibration method of camera using a constructed grid are developed. The experimental results, show that the required measurement accuracy specification is sufficiently satisfied using our proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.66-75
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• 2007

To prevent an insulator failure, an automatic cleaning and inspection robot was developed for suspension insulator strings. The robot autonomously moves along the insulator string using the clamps installed on its two moving frames. Especially, unlike the existing cleaning robots using jets of water, the robot system adopts a dry cleaning method using rotating brushes and a circular motion guide. In addition, a mechanized brush bristles and a voltage-balancing contactor are devised to increase cleaning efficiency and to prevent arc generation under live-line conditions, respectively. We confirmed its effectiveness through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2414-2417
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• 2005

Compact Camera Module(CCM) is widely used in PDA, Celluar phone and PC web camera. With the greatly increasing use for mobile applications, there has been a considerable demands for high speed production of CCM. The major burden of production of CCM is assembly of lens module onto CCD or CMOS packaged circuit board. After module is assembled, the CCM is inspected. In this paper, we developed the image capture board for CCM and the imaging processing algorithm to inspect the defects in captured image of assembled CCMs. The performances of the developed inspection system and its algorithm are tested on samples of 10000 CCMs. Experimental results reveal that the proposed system can focus the lens of CCM within 5s and we can recognize various types of defect of CCM modules with good accuracy and high speed.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.974-978
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.200-210
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• 2023

Until now, it is popular to use question-and-answer-based for human personality. The current inspection of representative personality types includes Myers-Briggs Type Indicator (MBTI) and job suitability evaluations. The problem of these inspection methods is influenced by the user's environment and psychological status during MBTI inspection. To solve this problem, we proposed MBTI Identification Model based on measuring bioelectricity patterns. We adapt traditional Korean medicine, the Eight Constitution, to this model. We develop an automatic MBTI identification algorithm that maps the Eight Constitution via biological current patterns to identify MBTI personality types. By utilizing the algorithm proposed in this research, it is anticipated that users will be able to measure MBTI more easily and accurately.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.556-567
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• 2021

Purpose: In this study, various methods of deep learning-based automatic damage analysis technology were reviewed based on images taken through Unmanned Aerial Vehicle to more efficiently and reliably inspect the exterior inspection and inspection of railway bridges using Unmanned Aerial Vehicle. Method: A deep learning analysis model was created by defining damage items based on the acquired images and extracting deep learning data. In addition, the model that learned the damage images for cracks, concrete and paint scaling·spalling, leakage, and Reinforcement exposure among damage of railway bridges was applied and tested with the results of automatic damage analysis. Result: As a result of the analysis, a method with an average detection recall of 95% or more was confirmed. This analysis technology enables more objective and accurate damage detection compared to the existing visual inspection results. Conclusion: through the developed technology in this study, it is expected that it will be possible to analysis more accurate results, shorter time and reduce costs by using the automatic damage analysis technology using Unmanned Aerial Vehicle in railway maintenance.

• Journal of the Semiconductor & Display Technology
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• v.14 no.1
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• pp.7-11
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• 2015

In this paper, an automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It is very difficult to determine focusing step size and moving direction in one camera autofocusing. The proposed method can improve speed and accuracy of focusing by using the optical axis interval of two cameras, which is automatically set up as focusing step size. Also, it can determine moving direction from focus value comparisons of two cameras, and then solve ambiguity of one camera focusing. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.