• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.271-275
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• 1996

In this paper, an automatic spot inspection system has been developed for camera target lens using the computer aided vision system. The developed system comprises: light source, magnifying optics, vision camera, XY robot, and a PC. An efficient algotithm for the spot detection has been implemented, thus up tof ew micrometer size spots can be effectively identified in real time. The developed system has been fully interfaced with XY robot systenm, PLCs, thus the practical spot inspection system has been implemented. The system has been applied to a practical camera manufacturing process, and showed its efficiency.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.189-192
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• 2008

Generally, the inspection is hard work and needs a lot of time. So, this work contains subjectivity of inspector owing to carry out the visual evaluations through naked eye. Thus, the result of inspection is not objective and reliable. The purpose of this study is to develop new inspection technique to solve above problems and to provide convenient inspection work. We make a new inspection system using digital image processing technology. This program can stitch each image and detect cracks of surface of concrete bridge. Also, It can extract an investigation drawing from the picture. Also, this program is a kind of management tools designed to have some functions such as converting the image data obtained from cameras to Data-Base format, searching and storing the data. At first, we try to make a automatic extracting program. But, changed by semiautomatic method because of various problems. Through field experiments, the application of this inspection system with specialty software has proven to be much faster, safer, and reliable than the inspections carried out by the naked eyes in managing safety of the bridges. The new inspection method may be able to make the inspection of bridge more efficient and reliable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7893-7901
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• 2015

It is important to the periodic collection and analysis of the maintenance and management information of bridges for a more safe and efficient management of the bridges. To enhance the reliability and ease of acquisition of the bridge inspection information that is the basis for a strategy for safe and economic management using the bridge management system (BMS), this study develops a smart phone application for bridge inspection and ensures the actual applicability of the application. The developed application that is linked with the BMS for life-cycle management of bridges is possible to real-time query, modify and transmit of the maintenance-related information, and the application is able to greatly relieve the time and cost for the bridge inspection through the automatic creation of site inspection reports. The proposed method using the application is directly or indirectly expected to be very high effects of value improvement, such as ease of use, improved accuracy, sustainability of information, and future utilization, compared to conventional inspection method.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.144-150
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• 2020

This study examined the current status of ATE in the development stage of the domestic guided weapons field, including the re-establishment of automatic test equipment (ATE), and attempted to develop methods to verify the validity of ATE in the defense sector. This study includes methods for confirming the repeatability and reproducibility of newly manufactured or replaced ATE. An error injection test is required for validation in the development phase. And pre-inspection steps are required for validation. When developing ATE, the use of an international standard testing script language ensures efficient validation and SW reliability. This ensures interoperability between the main and test equipment, and the tester can secure a test system platform that supports standardized testing methods, which is considered to be effective in validating specific ATE for each weapon system.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.377-383
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• 2021

In this paper, we describe the case of automatic test equipment development for hardware verification of stores management computer mounted on aircraft. Recently, the required functions of aircraft have been diversified and the related technologies of avionics equipment have developed, and the types and quantity of interfaces required for avionics equipment have increased. In addition to the existing old stores, the stores management computer also needs to control the interface in large quantities as the requirements for the new stores are added. For this reason, the time and manpower required for the inspection of avionic equipment are also increasing, and if the test process of avionic equipment can be automated and unmanned, more efficient inspection system operation will be possible. Therefore, this paper introduces the case of designing test software and test scenario to automate the structural design contents and verification process of test equipment required for the verification of hardware function of stores management computer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.997-1003
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• 2007

In this paper, we propose a global approach for automatic inspection of defects in the polarizer film image. The proposed method does not rely on local feature of the defect. It is based on a global image reconstruction scheme using the singular value decomposition(SVD). SVD is used to decompose the image and then obtain a diagonal matrix of the singular values. Among the singular values, the first singular value is used to reconstruct a image. In reconstructed image, the normal pixels in background region have a different characteristics from the pixels in defect region. It is obtained the ratio of pixels in the reconstructed image to ones in the original image and then the defects are detected based on the the statistical process of the ratio. The experiment results show that the proposed method is efficient for defect inspection of polarizer lam image.

• Journal of Platform Technology
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• v.11 no.6
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• pp.13-20
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• 2023

Regularly inspecting vehicle tires' condition is imperative for driving safety and comfort. Poorly maintained tires can pose fatal risks, leading to accidents. Unfortunately, manual tire visual inspections are often considered no less laborious than employing an automatic tire inspection system. Nevertheless, an automated tire inspection method can significantly enhance driver compliance and awareness, encouraging routine checks. Therefore, there is an urgency for automated tire inspection solutions. Here, we focus on developing a deep learning (DL) model to predict cracked tires. The main idea of this study is to demonstrate the comparative analysis of DenseNet121, VGG-19 and EfficientNet Convolution Neural Network-based (CNN) Transfer Learning (TL) and suggest which model is more recommended for cracked tire classification tasks. To measure the model's effectiveness, we experimented using a publicly accessible dataset of 1028 images categorized into two classes. Our experimental results obtain good performance in terms of accuracy, with 0.9515. This shows that the model is reliable even though it works on a dataset of tire images which are characterized by homogeneous color intensity.

• Journal of Fashion Business
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• v.1 no.2
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• pp.46-54
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• 1997

The purpose of this study is to understand women's wear manufacturing industries. First, the study was to investigate the present production systems and how much the automatic facility are by comparing them. This study enhanced more efficient, stable, and suitable work line. This intern will direct the way in which automatic facilities will be created. Second, through this study on the general character of the inspectors, the ratio of impaired goods, and the reasons for unsatisfactory goods, I intended to find out a way to decrease the impaired goods and to produce competitive and high quality goods. The results of the survey can be summarized as follows; 1. The result of the research on the automatic industrial facilities shows that the majority of the factories (77.4%) are 40% below the automatic facility rate. The reasons for this according to order are that was a deficit in money, no reason for expensive machines, and lack of the technique and the number of workers required to handle the machines. 2. At this time, the most required equipments are shown according to its importance; automatic sewing machine, automatic cutting machine, automatic spreading machine, and finishing & pressing machine. So in the women's wear manufacturing industries, they think that they need more automatic cutting machine, automatic spreading machine in the cutting field rather than high price automatic machine in the sewing field such as pattern former, pocket welting, automatic sleeve connecting machine and automatic label connecting machine. 3. The result of the research in the goods quality shows that the average impaired rate is 12.7% at the first inspection. In addition the average rate for complete impaired rate is 1.52%. The line system shows that it has a impaired rate that is double the rate of the pair system. Because of this, the industries plan to combine the line system and pair system to create an improved and suitable production system which can boost the quality and productivity of the goods. 4. The fabric is the main point of the impaired goods. The factors of the impaired goods in manufacturing are the lack of mental abilities of the worker, impaired fabrics and a lack of cooperation in the working system. Furthermore, there is a lack of technique for new material. 5. To prohibit impaired goods in manufacturing, there need to be a way to educate the workers and to enhance the workers' mind on the productive goods. Also there need to increase in the investments of automatic production machines. Finally there need to be a standardized working line. Therefore, there need to be an improvement on the management of the production of goods, the development of technique and an increase in the education for the workers, with this there will be a decrease in impaired goods, and an increase in better quality of goods to enforce the domestic apparel industries.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.159-165
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• 2017

In order to solve problems in automatic quality inspection of tablet capsules, computation-efficient image processing technique, appropriate threshold setting, edge detection and segmentation methods are required. And since existing automatic system for quality inspection of tablet capsules is of very high cost, it needs to be reduced through the realization of low-price hardware system. This study suggests a technique that uses low-cost camera module to obtain image and inspects dents on tablet capsules and sorting them by applying TLS curve fitting technique and edge-based image segmentation. In order to assess the performance, the major classifications algorithm of PCA, ICA and SVM are used to evaluate training time, test time and accuracy for capsule image area and curve fitting edge data sets.