• 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 the Korean institute of surface engineering
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• v.54 no.2
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• pp.84-89
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• 2021

The visual inspection method is widely used for corrosion damage analysis of steel plate due to the cost-efficient, fast and reasonably accurate results. However, visual inspection of corrosion deteriorated degree has a problem that the reliability of results differs depending on the inspector's individual knowledge and experience. In this study, we evaluated the degree of corrosion from a given image by using image segmentation method based on the grabcut and HSV(Hue, Saturation, Value) color image processing techniques for the development of an automatic inspection tool. The code written in Python based OpenCV-python libraries was used to categorize the images.

• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.90-95
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• 2007

Conventional bridge inspection involves the physical positioning of an inspector by the hydraulic telescoping boom of a "snooper truck" thereby providing visual access to bridge components. The process is time consuming, hazardous, and may be affected by lighting conditions, Therefore, it is of great interest that an automated and/or teleoperated inspection robot be developed to replace the manual inspection procedure. This paper describes the advanced bridge inspection robot system under development and other related activities currently undergoing at the Bridge Inspection Robot Development Interface (BIRDI). BIRDI is a research consortium with its home in the Department of Civil and Environmental System Engineering at Hanyang University at Ansan. Its primary goal is to develop advanced robot systems for bridge inspection and monitoring for immediate field application and commercialization. The research program includes research areas such as advanced inspection robot and motion control system, sensing technologies for monitoring and assessment, and integrated system for bridge maintenance. The center embraces 12 institutions, which consist of 7 universities, 2 research institutes, and 3 private enterprises. Research projects are cross-disciplinary and include experts from structural engineering, mechanical engineering, electronic and control engineering. This research project will contribute to advancement of infrastructure maintenance technology, enhancement of construction industry competitiveness, and promotion of national capacity for technology innovation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.445-446
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• 2007

The goal of this paper is accuracy improvement of appearance inspection by using image separation average value matching method. The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight can't bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we have used a average value matching in this paper for improvement of vision inspection accuracy and could increase inspection accuracy of vision system. In other words, we made an effort for elevation of vision inspection accuracy by making the identical image separation average value of reference image and input image. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.511-515
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• 1996

A remote controlled mobile robot system has been developed and tested to monitor the radiation area in the nuclear power plant. The mobile robot system operates according to car-driving-like commands and is capable of radiation measurement and visual inspection in unmanned situations under radiation. The robot system is equipped with a radiation sensor and two cameras with appropriate illumination set-ups. The camera with auto-focus function and 8-times zoom lens is mounted on the pan/tilt rotational base and the other is mounted on the front panel of the robot system. All commands regarding the motion of the mobile robot and various sensors are given through the monitoring system which is designed to provide an integrated man-machine interface.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.123-128
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• 2016

In manufacturing processing of a secondary battery, the visual inspection system is studied and developed to check the surface defects of the electrode plates. It consists of two parts, one is the hardware control and the other software implementation. The former is made up to the system configuration and the design of the optical system, the illuminations and the controllers. The latter is the detection algorithms of the surface defects. This system achieves the quality improvement of the electrode process and the price competitiveness. By using the proposed defects detection algorithms this system demonstrates the high reliability of spot, line, manhole, extraneous substance, scratch, and crater defect of a electrode plate surface.

• Journal of Korean Society of Steel Construction
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• v.11 no.1 s.38
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• pp.1-11
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• 1999

The aim of this study is to construct a machine vision monitoring system for an automatic visual inspection of weld joint in steel structure. An image processing algorithm for a visual weld defects detection on weld bead is developed using the intensity image. An optic system for getting four intensity images was set as a fixed camera position and four different illumination directions. The input images were thresholded and segmented after a suitable preprocessing and the features of each region were defined and calculated. The features were used in the detection and the classification of the visual weld defects. It is confirmed that the developed algorithm can detect weld defects that could not be detected by previously developed techniques. The recognized results were evaluated and compared to expert inspectors' results.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.9-18
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• 2000

This study includes noise automatic inspection system for washing machine auto-transmission one of modern home necessary. We effort to find and certificate sound noise source by sound power and sound intensity, and apply to frequency analysis in vibration related sound noise. still more we have been studying to data acquisition and programming for MS VisualBasic version 5.0. System component is below. 1) Pentium PC or data acquisition. 2) DSO for noise acquisition. 3)S/W for comparison and decision. 4) I/F Board for data communication. Wave form data through the DSO are converting to ASCII code data. The ASCII code through binary converting S/W. Finally we will making noise monitoring system and automatic inspection system.