• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.77-91
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• 2011

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by wavelet-based elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2E
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• pp.68-73
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• 2004

In the East Sea of Korea, the ocean environments are known to have strong variations in space and time. Their effects are very important factors in sound propagation and sonar performance. We consider the environmental factors such as eddies and thermal fronts affecting underwater sound propagation and target detection performance by sonars. Unfortunately, however, the detailed structure of eddies is usually difficult to understand by using the sea surface temperatures from infrared images alone or a few profiles from the CTD (conductivity, temperature and depth) castings. The temperature fields of eddy and thermal front are simulated with typical patterns of those obtained from several observations. This paper delivers the overviews of environments and acoustic models with their simulation results on sonar performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.315-317
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• 2012

본 논문에서는 인체의 골격 위치와 깊이 정보를 사용하여 주위 환경에 강건한 특성을 지니는 움직이는 사람 영역 검출 방법을 제안한다. 먼저 영상 내에서 인체의 골격 위치를 검출한 다음 인체 골격의 중심이 될 수 있는 지점에 대해 인체의 평균적 깊이 범위 내에서 깊이 세분화를 수행한다. 그리고 깊이 세분화를 통하여 검출된 사람 영역의 후보군에 대해 윤곽선 기반의 움직임 검출기법을 사용하여 후보군 내에서 움직이는 사람에 해당하는 특징점을 검출한다. 마지막으로 잡음 제거 및 움직이는 사람에 해당하는 영역 검출을 위하여 개선된 깊이 세분화 과정을 수행한다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.2
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• pp.86-93
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• 2016

To find the buried pipes and cavities, GPR detection were proceed by the type and depth of underground pipes and cavities buried in the Chamber. In the case of asphalt pavement and non-pavement, the exploration of buried pipe were easy than the concrete and reinforced concrete pavement. In the case of air cavity, the buried depth of 1 m was evaluated as the detection was possible.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.600-602
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• 2019

Metals are used in a variety of industrial sites and daily life. Metals are often used in machinery, automobile parts, wires, and robots. Metal causes small damage to the metal surface for a variety of reasons, such as the processing process and the user's operating environment. In this paper, phase detection for the inspection of defects in metals has been implemented. Using the electrical conductivity of metal, a circuit whose phase varies with the depth and size of the defect, and with the changed phase, the depth and size of the defect can be estimated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.243-248
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• 2014

This study presents an investigation into the ways to detect the areas of object movement with Kinect's Depth Frame, which is capable of receiving 3D information regardless of external light sources. Applied to remove noises along the boundaries of objects among the depth information received from sensors were the blurring technique for the x and y coordinates of pixels and the frequency filter for the z coordinate. In addition, a clustering filter was applied according to the changing amounts of adjacent pixels to extract the areas of moving objects. It was also designed to detect fast movements above the standard according to filter settings, being applicable to mobile robots. Detected movements can be applied to security systems when being delivered to distant places via a network and can also be expanded to large-scale data through concerned information.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.395-399
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• 2006

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of unpaved trail are included in this paper.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.6-9
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• 2008

A 3D depth measurement system is proposed for mobile vehicles. Depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to- the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Non-linear trail are included in this paper.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.681-688
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• 2016

In the intelligent video surveillance, recognizing the moving objects is important issue. However, the conventional moving object recognition methods have some problems, that is, the influence of light, the distinguishing between similar colors, and so on. The recognition methods for the moving objects using depth information have been also studied, but these methods have limit of accuracy because the depth camera cannot measure the depth value accurately. In this paper, we propose a recognition method for the moving objects by using both the depth and the color information. The depth information is used for extracting areas of moving object and then the color information for correcting the extracted areas. Through tests with typical videos including moving objects, we confirmed that the proposed method could extract areas of moving objects more accurately than a method using only one of two information. The proposed method can be not only used in CCTV field, but also used in other fields of recognizing moving objects.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.193-199
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• 2015

Active thermography techniques have the capability of inspecting a broad range simultaneously. By evaluating the phase difference between the defected area and the healthy area, the technique indicates the qualitative location and size of the defect. Previously, the development of the defect detection method used a variety of materials and the test specimen was done. In this study, the proposed technique of lock-in is verified with artificial specimens that have different size and depth of subsurface defects. Finally, the defect detection capability was evaluated using comparisons of the phase image and the amplitude image according to the size and depth of defects.