• Computers and Concrete
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• v.3 no.1
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• pp.29-42
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• 2006

In this study, a novel education system for inspection of concrete bridges is presented. The new education approach uses virtual reality (VR) and three-dimensional computer graphics (3DCG) in training engineers to become bridge inspection specialists. The slow time-dependent deterioration of concrete bridges can be reproduced on the computer screen in any chosen time frame, thus providing the trainees with illustrative and educative insight into the deterioration problem. In the proposed VR/3DCG approach a three-dimensional model of concrete bridge, including surfaces, viewpoints and walkthrough paths is created. With the help of this virtual bridge model, an experienced bridge inspection specialist teaches the different deterioration phenomena of concrete bridges to the trainees. The new system was tested, and the inspection results from the case bridge showed that in comparison with the traditional Japanese bridge inspection education system, the new system gives better results. In addition to the improvement of quality of bridge inspections, the new VR/3DCG system-based education brings along some other, more intangible benefits.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1099-1104
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• 2013

This paper presents a learning-based visual inspection method that addresses the need for an improved adaptability of a visual inspection system for parts verification in panorama sunroof assembly lines. It is essential to ensure that the many parts required (bolts and nuts, etc.) are properly installed in the PLC sunroof manufacturing process. Instead of human inspectors, a visual inspection system can automatically perform parts verification tasks to assure that parts are properly installed while rejecting any that are improperly assembled. The proposed visual inspection method is able to adapt to changing inspection tasks and environmental conditions through an efficient learning process. The proposed system consists of two major modules: learning mode and test mode. The SVM (Support Vector Machine) learning algorithm is employed to implement part learning and verification. The proposed method is very robust for changing environmental conditions, and various experimental results show the effectiveness of the proposed method.

• Journal of Preventive Medicine and Public Health
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• v.45 no.2
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• pp.78-89
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• 2012

Objectives: Although vaccination rates have increased, problems still remain in the storage and handling of vaccines. This study focused on inspecting actual vaccine storage status and awareness, and comparing them before and after education was provided. Methods: In the primary inspection, a status survey checklist was completed by visual inspection. A questionnaire on the awareness of proper vaccine storage and handling was also administered to vaccine administrators in private medical institutions in 4 regions in Gyeongsangbuk-province. One-on-one education was then carried out, and our self-produced manual on safe vaccine storage and management methods was provided. In the secondary inspection, the investigators visited the same medical institutions and used the same questionnaire and checklist used during the primary inspection. The results before and after education were compared, by treating each appropriate answer as 1 point. Results: The average checklists score was 9.74 (out of 15 points), which increased significantly after education was provided (by 0.84, p<0.001). The participants demonstrated improved practices in recording storage temperatures(p=0.016), storing vaccines in the center of the refrigerator (p=0.004), storing vaccines with other medication and nonmedical items (p=0.031) after education. The average score calculated from the questionnaires was 10.48 (out of 14points), which increased after education (by 1.03, p<0.001). Conclusions: This study suggests that vaccine storage practices and awareness are inadequate, but can be partially improved by providing relevant education. Repetitive education and policy-making are required to store vaccines safely because one-off education and unenforced guidelines offer limited efficacy.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.17-22
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• 2011

LEDs(Light Emitting Diodes) are becoming widely used and increasingly in demand. Quality inspection of the LEDs has become more important. Two-dimensional inspection systems are limited in inspection capability, so threedimensional(3-D) inspection systems are needed. In this paper, a cost-effective and simple 3-D measurement system of LED packages using phase measuring profilometry(PMP) is proposed. The proposed system uses a pico projector to project sinusoidal fringe patterns and to shift phases instead of piezocrystal. It was evaluated using extremely accurate gauge blocks, yielding excellent repeatability of about 12 um(3-sigma). 3-D measurements of various LED packages were performed to demonstrate the applicability and efficiency of the proposed system.

• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.45-51
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• 2012

Multilayer co-extrusion blown film construction is a popular technique for producing plastic films for various packaging industries. Automated detection of defective films can improve the quality of film production process. In this paper, we propose a film inspection system that can detect and classify film defects robustly. In our system, first, film images are acquired through a high speed line-scan camera under an appropriate lighting system. In order to detect and classify film defects, an inspection algorithm is developed. The algorithm divides the typical film defects into two groups: intensity-based and texture-based. Intensity-based defects are classified based on geometric features. Whereas, to classify texture-based defects, a texture analysis technique based on local binary pattern (LBP) is adopted. Experimental results revealed that our film inspection system is effective in detecting and classifying defects for the multilayer co-extrusion blown film construction line.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.127-132
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• 2019

In this paper, we propose a visual inspection method of automotive parts for injection molding to improve the appearance quality and productivity of automotive parts. Exterior inspection of existing injection molding automobile parts was generally done by manual sampling inspection by human. First, we applied the edge-tolerance vision inspection algorithm ([1] - [4]) for vision inspection of electronic components (TFT-LCD and PCB) And we propose a new visual inspection method to overcome the problem. In the proposed visual inspection, the inspection images of the parts to be inspected are aligned on the basis of the reference image of good quality. Then, after partial adaptive binarization, the binary block matching algorithm is used to compare the good binary image and the test binary image. We verified the effectiveness of the edge-tolerance vision check algorithm and the proposed appearance vision test method through various comparative experiments using actual developed equipment.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.97-102
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• 2011

Lots of 2D vision algorithms have been applied for inspection. However, these 2D vision algorithms have limitation in inspection applications which require 3D information data such as the height of semiconductor chips. Stereo vision is a well known method to measure the distance from the camera to the object to be measured. But it is difficult to apply for inspection directly because of its measurement error. In this paper, we propose two adjustment methods to reduce the error of the measured height data for stereo vision. The weight value based model is used to minimize the mean squared error. The average value based model is used with simple concept to reduce the measured error. The effect of these algorithms has been proved through the experiments which measure the height of semiconductor chips.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• Journal of The Korean Association of Information Education
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• v.13 no.1
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• pp.50-59
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• 2009

This research pursued improvement of learning motives and accomplishment of study by developing storytelling based education model and applying them to field for elementary students study of programming. As a result of inspection on study motives, two groups showed statistically significant different with experiment group showing higher average than comparison group. As a result of inspection on study accomplishment, both groups showed improved average points over previous inspection, and particularly experiment group showed higher average than that of comparison group The results of this research showed that storytelling strategy has direct relation with improvement of programming study motives and study accomplishment