• Proceedings of the Korea Concrete Institute Conference
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• 2001.05a
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• pp.783-788
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• 2001

Voids created with concrete construction or deterioration result in serious weakness from the aspects of both structural and durable function. Ultrasonic method using image processing technique was used for detecting pattern of voids in concrete in this study Experimental investigation was carried out for three types(patterns) of void in concrete. The effect of curing period of concrete and ultrasonic measurement method was also investigated. As a result it has been verified that the semi-direct measurement method is more effective than the other methods for detecting pattern of voids in concrete in ultrasonic method using image processing technique. The longer the curing period of concrete is, the better the detection accuracy of void pattern can be obtained.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.196-202
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• 1999

Recent trend changes a criterion for evaluation of burner that environmental problem is raised as global issue. For efficient driving problem, the higher thermal efficiency and the lower oxygen in exhaust gas, burner is evaluated the better. For environmental problem, burner must satisfy $NO_{X}$ limit and CO limit. Consequently, 'good burner' means on whose thermal efficiency is high under the constraint of $NO_{X}$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop feedback control scheme whose output is the consistency of $NO_{X}$ and CO. This paper describes development of real time flame diagnosis technique that evaluate and diagnose combustion state such as consistency of components in exhaust gas, stability of flame in quantitative sense. This study focuses on wave length of luminescence from chemical reaction measurement of the luminescence via optical measuring apparatus and derive correlation with consistency of components in exhaust gas by image processing technique.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.450-452
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• 1995

The Tree observation technique is being highlighted as a research area for deterioration of insulation because of high-voltage power system. For the measurement of tree, image processing is actively studied as a experimental technique of electrical tree, because the conventional directed visual method is impossible to analyze on tree degradation area and tree pattern. In this paper, we have developed the tree measuring system using image processing. By using an image processing technique, the treeing can be easily measured and effectively observed.

• Progress in Superconductivity and Cryogenics
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• v.15 no.1
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• pp.25-28
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• 2013

We report processing technique in the MO image measurement system. Calibration procedure is not only considered to perpendicular field but also in-plane field. Current density and field profiles are obtained by Biot-savart law and inversion method. We show example of $(Gd,Y)_1Ba_2Cu_3O_{7-{\delta}}-BaZrO_3$ film that have tilted nano rod pinning centers about $13^{\circ}$ from the c-axis.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.345-346
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• 2009

The segmentation of vessel including portal vein, hepatic vein and artery, from Computed Tomography (CT) images plays an important role in the therapeutic strategies for hepatic diseases. Representing segmented vessels in three dimensional spaces is extremely useful for doctors to plan liver surgery. In this paper, proposed method is focused on smoothing technique of segmented 3D liver vessels, which derived from 3D region growing approach. A pixel expand algorithm has been developed first to avoid vessel lose and disconnection cased by the next smoothing technique. And then a binary volume filtering technique has been implemented and applied to make the segmented binary vessel volume qualitatively smoother. This strategy uses an iterative relaxation process to extract isosurfaces from binary volumes while retaining anatomical structure and important features in the volume. Hard and irregular place in volume image has been eliminated as shown in the result part, which also demonstrated that proposed method is a suitable smoothing solution for post processing of fine vessel segmentation.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1455-1464
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• 2006

In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.240-250
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• 1988

This pc-vision system digitizes/displays 512*512*8 bit pixel image in real time and is capable of the various image processing. This system provides a versatile solution to those users pursuing high performance image processing system compatible with the VME bus, and is general purpose imaging system giving the optimal efficiency for machine vision, medical use and various task. In this paper, Image processing technique has classified image enhancement and image analysis in order to design and implement the pc-vision system. In order to improve processing speed, This system unilizing ROI processing performs point operation, local operation and global operation as well as common arithmetic/logic operation in real time.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.182-191
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• 2005

It is very important to obtain a high quality of bone image for an accurate ultrasonic measurement of bone mineral density. In this study, we suggested a technique to acquire an optimal image by adapting an acoustic lens and a properly selected ultrasonic probe. Also, we have applied an image processing algorithm with which automatically makes a decision of brightness and contrast of image by generating threshold level, a composition of ultrasonic data, an elimination of noise using modified median filter, and a real time interpolation. We could confirm much improved resolution of bone image with acoustic lens attached to the ultrasonic probe and with the image processing algorithm suggested in this study. Therefore, it became possible to precisely diagnose the osteoprosis using ultrasonic imaging technique.