• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1089-1095
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• 2010

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.392-399
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• 2010

The Automobile has developed and changed through the years from the invention and increased human-being's scope of activity. Junction Box, one of the part of automobile, is inspected by human eyes which caused mistakes and slow progress. To achieve the speed and accuracy the system was compensated by vision system which is inspecting automatically. This paper is automatic inspection of fuse and relay which is inserted in the junction box by checking the color and pattern of the cover. After checking the performance of the system by using the junction box, the result was 100 percent perception and open the possibility to inspect junction box fast and easy and accurate if it is applied to the industry.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.619-625
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• 2015

There is a large interest to find reliable and automatic methods for crack detection and quantification in the railway bogie frame. The non-destructive inspection of railway bogie frame has been performed by ultrasonic and magnetic particle testing in general inspection. The magnetic particle method has been utilized in the defect inspection of the bogie frame but the grinding process is required before inspection and the dust is developed resulting from the processing. The objective of this paper is to apply the inspection method of bogie frame using infra-red thermography. The infra-red thermography system using the excitation of eddy current was performed for the defect evaluation of weld specimen inserted artificial defects. The result shows that the infra-red thermography method can detect the surface and inner defects in weld specimen for bogie frame.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.5
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• pp.8-14
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• 2008

For nondestructive inspection of electron beam (EB) welding part in automotive power transmission assembly, a pulse-echo ultrasonic testing apparatus in water immersion has been applied using the ultrasonic waves with a frequency of 10MHz. However various problems have appeared during the ultrasonic inspection, which led to some significant mistakes in automatic quality evaluation of the welding parts. Experimental study showed that the state of water couplant medium containing some amount of contaminants, rusts and anti-corrosion agents had considerable influences on the reduction of ultrasonic amplitudes during wave propagation. The amplitude reduction depending on the coupling medium state could bring about some mis-diagnoses for defects in the welding parts. The results proposed that for a reliable inspection of defects in welds the state of water medium should be kept in about 15 volume fractions (vol.%) of anti-corrosion agents and in minimized contaminants.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.188-193
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• 2008

According to introduce KTX in Korea, rail-road bridge section of KTX was increased approximately 50% of the total length. Bridge is required periodic inspection and check to prevent accident and hazard because various damage which have effects on traffic and replacement of damaged parts is difficult. Specifically, the train as large-scale transportation because accidents led to great damage, preventing these accidents are critical. Well-organized management and maintenance systems are required to prevent the accidents. In the case of roadway bridge, bridge inspection vehicle is used to deploy inspectors in roadway bridge. However, this method requires a lot of time and efforts, and inspectors are exposed to potential hazard. Also, surrounding environment like poor lighting system or electric wire could harm the inspector while repairing. Due to this reason, automatic repairing and inspecting system have been introduced to replace the old methods. Management system of the railroad bridge track for trains uses various advanced equipments, but whereas roadway bridge management system is lacking these efforts. As a result of that, this study looks over the existing management method. and review the method to apply the Bridge Inspection Robot in railroad bridge. Moreover, this study suggests future management technology using inspection robot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1257-1263
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• 2006

Many automatic medical devices have been invented and developed mostly for the western medicine, not for the oriental medicine. Facial ocular inspection is one of the four diagnosis methods of oriental medicine, which makes a diagnosis of disease by observing the shape and color of patient's vital organs. In facial ocular inspection, the regions of five sensory organs and Myungdang are specially important. In this paper, we propose a novel method to extract the five sensory organ and Myungdang from a facial image for facial ocular inspection. Finally, we show the usefulness of the proposed method by experiments.

• Journal of the Korean Institute of Gas
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• v.19 no.2
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• pp.45-53
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• 2015

In order to improve the performance of the visual inspection process, in addition to existing automatic visual inspection machine and human inspectors have developed a new process configuration using a Naive Bayes classifier. By applying the classifier, defect leakage and human inspector's work amount could be improved at the same time. New classification method called AMPB was applied instead of conventional methods based on MAP classification. By experimental results using the filter product for camera modules, it was confirmed that it is possible to configure the process at the level of leakage ratio 1.14% and human inspector's work amount ratio 75.5%. It is significant that the result can be applied in such a wide range as gas leak detection which is the collaboration process between inspection machine and human inspector's

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.359-363
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• 2017

The LED (Liquid Emitting Diode) frame device is a big part of the representative display industry in Korea. LED is an essential part for TV, monitor, notebook, and mobile phone. In Japan, Taiwan, China and other countries, investment in LEDs has been strengthened, and productivity has become an important issue. However, as the size of the parts becomes smaller, the inconsistent inspection by the human eye becomes a problem of reliability, so that the automatic inspection process becomes an essential issue in the field of LED module inspection. In this paper, we investigate defects in visual inspection process using computer vision technology. The inspection of the LED frame is made quickly and accurately, thereby improving the efficiency of the process and shortening the inspection time. As a result of applying the inspection system to the field, we confirmed that it is possible to inspect quickly and accurately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3416-3422
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• 2014

A shock absorber rod is located in the center of the absorber piston and is responsible for the reciprocating movement portion. If it has surface defects, the damping performance of product will be adversely affected. A rod surface has gloss by heat treatment. Therefore, it is difficult to find a defect, such as dust, imprints, and blowholes. Because a total inspection is achieved by visual inspection by workers, it causes eyestrain and the quality of the product is not constant. In this paper, a machine vision system was developed to find a defect using a line-scan camera. The machine can detect surface defects than 0.3mm. To minimize the occurrence probability of defects on the inspection process, the developed auto inspection system had an automatic feeding system and incorporated a protection system. Through the development of this system, which relies on the operator's visual inspection of the surface of the shock absorber, the Rod inspection system constructed quality inspection standards and standardized tests to ensure improved reliability.

• Smart Structures and Systems
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• v.24 no.5
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• pp.669-681
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• 2019

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).