• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.355-360
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• 2013

With the modern machinery towards the direction of high-speed development, the thermal issues of mechanical transmission system and its components is increasingly important. Ball bearing is one of the main parts in rotating machinery system, and is a more easily damaged part. In this paper, bearing thermal fault detection is investigated in details Using infrared thermal imaging technology to the operation state of the ball bearing, a preliminary thermal analysis, and the use of numerical simulation technology by finite element method(FEM) under thermal conditions of the bearing temperature field analysis, initially identified through these two technical analysis, bearing a temperature distribution in the normal state and failure state. It also shows the reliability of the infrared thermal imaging technology. with valuable suggestions for the future bearing fault detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.545-551
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• 2016

Surface temperature of supersonic wind tunnel model was measured using an infrared thermography technique. To measure the temperature quantitatively, various calibration techniques such as blackbody calibration which converts detected camera signal to temperature, distortion correction due to the camera lens and an imbalance of camera pose, and emissivity calibration which considers viewing angles to the model surface, were employed. Throughout the study, for the quantitative as well as qualitative surface temperature measurement, it was verified that the distortion correction must be considered even for the use of two-dimensional model in aerodynamics testing.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.127-133
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• 2011

A LabVIEW program has been developed together with simple infrared thermography(IRT) system to control the lock-in conditions of the system efficiently. The IR imaging software was designed to operate both of infrared camera and halogen lamp by synchronizing them with periodic sine signal based on thyristor(SCR) circuits. LabVIEW software was programmed to provide users with screen-menu functions by which it can change the period and energy of heat source, operate the camera to acquire image, and monitor the state of the system on the computer screen. In experiment, lock-in IR image for a specimen with artificial hole defects was obtained by the developed IRT system and compared with optical image.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.329-336
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• 2022

Unreadable Khitan scripts of ancient documents written by indian ink on parchment(sheepskin) are visualized by active infrared thermography without contacting and damaging the document which are deteriorated and aged presumably over many years. Sinusoidal infrared thermal wave using Halogen lamp is applied to the surface of the document in order to selectively magnify and record the thermal response of indian ink. The infrared image of the document captured in real time by infrared camera under the active external excitation shows the better sharpness and readability of Khitan characters than the optical image, from which many Khitan letters like ' ' and ' ' sounding as 'd' and 'ri' in English alphabet are detected and deciphered. It is concluded from the experiment that the active infrared thermography can be used as a promising method for digital reconstruction and preservation of ancient documents in the future.

• The Optical Journal
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• s.141
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• pp.21-23
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• 2012

신종플루의 전 세계적 유행과 함께 적외선 광학계는 일반인에게 익숙한 기술이 되었다. 스웨덴에서 최초로 개발된 적외선 카메라는 현재 군수용뿐만 아니라 보안, 의료, 차량, 재난구조 등 다양한 분야에 적용되고 있다. 이런 민간분야 시장 성장에는 핵심부품인 적외선 렌즈와 IR Detecter의 가격 인하가 가장 큰 역할을 하고 있다. 특히 차량용 적외선 카메라의 채용은 관련시장을 폭발적으로 성장시킬 가능성을 인정받고 있으며 이런 흐름은 다시 관련 분야의 가격 인하요인으로 강력히 작용하고 있다. 아래표의 적외선 광학계의 수요 산업군 메가 트렌드(<적외선 수요 산업군> 표)는 자동차, 플랜트, 보안, 소방방재, 방위산업 등 다양한 분야의 적외선 광학관련 수요를 포함하고 있어 향후 주요 산업군으로 부각될 것으로 예상된다. 특히 저가양산이 가능해 다양하게 주목받고 있는 성형방식 적외선 광학렌즈 관련 주요 해외 선진업체의 기술수준은 적외선 원천소재를 제외하고는 국내에도 이미 세계수준의 기술을 보유하고 있으며, IR Detector 관련 기술 역시 냉각식 및 비냉각식 분야에서 세계최고 수준의 원천기술을 보유 중이어서 국내 업체의 양산화 기술이 완성되면 관련 세계 시장 선점이 가능하며 향후 5년이 이를 결정짓는 중요한 시점이 될 것이다.

• Annual Conference of KIPS
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• 2019.10a
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• pp.8-10
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• 2019

열화상 장비는 빛이 없는 암흑 상태에서도 물체에서 발산하는 적외선을 탐지하여 이를 영상으로 제공하는 장비이다. 이러한 장점으로 기존 활용되던 군사 분야와 더불어 자동차 및 감시시스템 등 다양한 민수 분야로 활용분야가 넓어지고 있다. 따라서 기존 방식인 FPGA 기반 열화상 이미지 모듈은 민수 시장의 다양한 요구사항과 환경을 반영하기에는 힘들 실정이다. 그에 따라 FPGA 기반 시스템의 단점을 보완하고 추가적인 요구사항을 만족하는 시스템의 필요성이 대두되었다. 본 논문에서는 상용 이미지 프로세서 기반 열화상 이미지 처리 모듈을 제안한다. 기존 FPGA 기반 열화상 이미지 처리 방식이 아닌 상용 이미지 프로세서 기반 구조 설계로 함으로써 다양한 영상 입·출력 인터페이스 수신 및 표준 영상 출력 포멧을 지원한다. 따라서 상용 프로세서 기반 열상 처리 모듈을 통한 시스템 개발 시 뛰어난 접근성으로 시스템 구축이 용이하고 다양한 요구사항 적용이 가능함에 따라 개발 기간 및 비용 단축, 다양한 응용에 사용이 가능할 것으로 예상한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.9-12
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• 2019

지난 수 년 동안 계속해서 일반 실상 카메라를 이용한 영상분석기술에 대한 연구가 활발히 진행되고 있다. 최근에는 딥러닝 기술을 적용한 지능형 영상분석기술로 발전해 왔으며 국방기지방호, CCTV, 사용자 얼굴인식, 머신비전, 자동차, 드론 산업이 활성화되면서 많은 시너지를 효과를 일으키고 있다. 그러나 어두운 밤과 안개, 날씨, 연기 등 다양한 여건에서 따라서 카메라의 영상분석 정확성 감소와 오류가 수반될 수 있으며 일반적으로 딥러닝 기술을 활용하기 위해서는 고사양의 GPU를 필요로 하기 때문에 다른 추가적인 시스템이 요구된다. 이에 본 연구에서는 열적외선 영상의 객체 검출에 적용하기 위해 SSD(Single Shot MultiBox Detector) 기반의 경량적인 MobilNet 네트워크로 재구성하여, 모바일 기기 등 낮은 사양의 낮은 임베디드 시스템에서도 활용 할 수 있는 방법을 제안한다. 모의 실험결과 제안된 방식의 모델은 적외선 열화상 카메라에서 객체검출과 학습시간이 줄어든 것을 확인 할 수 있었다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.95-102
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• 2007

It needs to Prevent damage as aging shotcrete itself exists as a dangerous component to comuting vehicles or infrastructure due to scaling, spaling, and loosening. However, it is hard to make an approach owing to a steep slope and high work, and there has been indicated a limit that it is difficult to grasp the internal condition of shotcrete on the surface. This study aimed to research internal defects that cannot be observed from the surface, by measuring a subtle thermal transfer on the shotcrete surface by using infrared thermography for overcoming such a technical limit. As a result of conducting an inspection through an analysis on measured data and fieldwork using an endoscope camera, it was impossible to accurately determine the wet part because of an excessive coating of shotcrete, yet, This study is proposed effictively extract a void part of the inside with non-destructive and non-touching method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.