• Title/Summary/Keyword: Thermal Image

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Manufacture of Aspheric Lens Using Thermal Image Optics (열영상 광학계용 비구면 렌즈 제작)

  • Kim, Dae-Jung;Gu, Hal-Bon;Kim, Shang-Suk;Kim, Jeong-Ho
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.07a
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    • pp.191-194
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    • 2003
  • Through using aspheric lens can result in advantages such as an improved optical transfer function, a reduced distortion path or the realization of special image field curvatures. Using the diamond turning method for generating aspherics, the company claim to be able to generate surfaces with a form error of less than $0.33\;{\mu}\;m$ and a surface roughness of less than $0.025\;{\mu}\;m$. In this paper, we are manufacturing thermal image aspheric lens. Thermal image system is electro-optical imaging device which can make visible the difference of infrared energy naturally emitted by objected. In the result of aspherical surface, the form accuracy of about $0.24\;{\mu}\;m$ P-V was obtained and the surface roughness Ra $0.004\;{\mu}\;m$. Also, a brief review of Ultra-precision system Korea photonics technology institute(KOPTI) is present in this paper.

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Study on the Effect of Emissivity for Estimation of the Surface Temperature from Drone-based Thermal Images (드론 열화상 화소값의 타겟 온도변환을 위한 방사율 영향 분석)

  • Jo, Hyeon Jeong;Lee, Jae Wang;Jung, Na Young;Oh, Jae Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.1
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    • pp.41-49
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    • 2022
  • Recently interests on the application of thermal cameras have increased with the advance of image analysis technology. Aside from a simple image acquisition, applications such as digital twin and thermal image management systems have gained popularity. To this end, we studied the effect of emissivity on the DN (Digital Number) value in the process of derivation of a relational expression for converting DN to an actual surface temperature. The DN value is a number representing the spectral band value of the thermal image, and is an important element constituting the thermal image data. However, the DN value is not a temperature value indicating the actual surface temperature, but a brightness value indicating high and low heat as brightness, and has a non-linear relationship with the actual surface temperature. The reliable relationship between DN and the actual surface temperature is critical for a thermal image processing. We tested the relationship between the actual surface temperature and the DN value of the thermal image, and then the radiation adjustment was performed to better estimate actual surface temperatures. As a result, the relation graph between the actual surface temperature and the DN value similarly show linear pattern with the relation graph between the radiation-controlled non-contact thermometer and the DN value. And the non-contact temperature after adjusting the emissivity was closer to the actual surface temperature than before adjusting the emissivity.

Efficient Control of an Air Conditioner Using Thermal Image and a Fuzzy Control Method (퍼지 제어 기법과 열 영상을 이용한 에어콘의 효율적 제어)

  • Kim, Kwang-Baek;Woo, Youn-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.10
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    • pp.2201-2206
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    • 2010
  • The shortage of fossil fuel drives researchers to find a new way to increases energy efficiency. In this paper, we propose a method to control the direction and speed of an air conditioner using a thermal image and fuzzy controlling method, which results in the increase of energy efficiency. The thermal image is first converted into a color temperature image which represents the temperature range from $24.0^{\circ}C$ to $27.0^{\circ}C$. The temperature image is divided into 5 columns and the distribution of them is used to analyze room temperature and control an air conditioner. The proposed method was applied to 300 by 400 thermal images. When the performance of the proposed method was compared to existing systems in energy efficiency, the proposed method was better than existing methods, which is clear from experimental results.

A Study on Application of Remote Sensing for Thermal Plume Analysis (온배수 확산분석을 위한 Remote Sensing 활용에 관한 연구)

  • Yeu, Bock-Mo;Cho, Gi-Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.1 no.2 s.2
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    • pp.185-194
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    • 1993
  • In this research, the image obtained by TM platformed in the LANDSAT-5 and the terrestrial infrared image obtained by the Thermo Tracer were employed in order to search the distribution of industrial thermal plume discharged into seas. Sea surface temperature distributions were deduced based on the infrared band 6 in the TM image of the LANDSAT by employing the transformal formula provided by the CSFC of the NASA and post-calibration values. The temperature distributions were also obtained with the processing mode of the TH1100 series from the terrestrial thermal image or the Thermo tracer. According to the results of the image analyses with this methods, it was found that sea surface temperatures in shallow coastal area largely affected by the temperatures of the freshwater and inland and that the range and the area of distribution of the thermal plume can be visualized quantitatively. Furthermore, when the terrestrial thermal infrared scanner is used, the more details of the distribution range can be obtained, and the image results are comparable to those obtained from the LNADSTA.

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Analysis of Water Stress of Greenhouse Crops Using Infrared Thermography (열영상 정보를 이용한 온실 재배 작물의 수분 스트레스 분석)

  • 김기영;류관희;채희연
    • Journal of Biosystems Engineering
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    • v.24 no.5
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    • pp.439-444
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    • 1999
  • Automated greenhouse production systems often require crop growth monitoring involving accurate quantification of plant physiological properties. Conventional methods are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system can accomplish rapid and accurate measurements of physiological-property changes of stressed crops. In this research a thermal imaging system was used to measure the leaf-temperature changes of several crops according to water deficit. Thermal images were obtained from lettuce, cucumber, pepper, and chinese cabbage plants. Results showed that there were significant differences in the temperature of stressed plants and non-stressed plants. The temperature differences between these two group of plants were 0.7 to 3$^{\circ}C$ according to species.

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A Study on the Degradation of Insulators using Thermal Image Camera (열상카메라를 이용한 애자의 열화에 관한 연구)

  • Kim, Jeong-Tae;Kim, Ji-Hong;Koo, Ja-Yoon;Yoon, Ji-Ho;Ham, Gil-Ho
    • Proceedings of the KIEE Conference
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    • 2000.07c
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    • pp.1933-1935
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    • 2000
  • In this paper, it was tried to find out the minimum measurement range in the diagnosis of insulators using thermal image camera, for the purpose, leakage currents and thermal images were observed simultaneously for the insulators of which surface had been artificially polluted by salt fog. As a result. the surface temperature was increased with leakage currents. Also, the results of AC breakdown tests for the insulator of which temperature rise was more than 1 $^{\circ}C$ showed to be bad. Therefore, through the study on the relationship between leakage current, temperature rise and AC breakdown voltages, the diagnosis of the insulator in site would be possible using the thermal image camera.

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A study on the application of Plateau equalization algorithm for contrast enhancement of real-time thermal image (Plateau equalization 알고리즘을 적용한 실시간 열영상 대조비 개선에 관한 연구)

  • Cho Heung-Gi;Kim Soo-Gon;Lee Jeong-Bok;Lee Won-Sun;Jeon Hee-Hong
    • Proceedings of the KIPE Conference
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    • 2002.11a
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    • pp.186-189
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    • 2002
  • Real-time thermal image is obtained by thermal imaging systems measuring radiant emittence according to law of Plank's blackbody radiation. The histogram of thermal image is not uniform. The signal bands of background and target are separated and grouped in narrow bands. In such a system, contrast enhancement indispensible to distinguish target from background. In this study, plateau histogram equalization using local histogram is proposed for contrast enhancement.

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Visible Light and Infrared Thermal Image Registration Method Using Homography Transformation (호모그래피 변환을 이용한 가시광 및 적외선 열화상 영상 정합)

  • Lee, Sang-Hyeop;Park, Jang-Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.6_2
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    • pp.707-713
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    • 2021
  • Symptoms of foot-and-mouth disease include fever and drooling a lot around the hoof, blisters in the mouth, poor appetite, blisters around the hoof, and blisters around the hoof. Research is underway on smart barns that remotely manage these symptoms through cameras. Visible light cameras can measure the condition of livestock such as blisters, but cannot measure body temperature. On the other hand, infrared thermal imaging cameras can measure body temperature, but it is difficult to measure the condition of livestock. In this paper, we propose an object detection system using deep learning-based livestock detection using visible and infrared thermal imaging composite camera modules for preemptive response

Tensile characteristics of Alumina Thin Film at High Temperature (고온에서 알루미나 박막의 인장특성)

  • 선신규;강기주
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.1344-1347
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    • 2004
  • Recently, Study on measuring property of a micro thin film(nm ~ hundreds of ) under Thermal Mechanical loading. In this work, We perform tensile test at high temperature(1200 ) to investigate mechanical properties of alumina TGO formed under Thermal Barrier Coating. We used Digital Image Correlation method for measuring displacement, and We presented a method of tensile test for thin film at high temperature.

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Enhancing Single Thermal Image Depth Estimation via Multi-Channel Remapping for Thermal Images (열화상 이미지 다중 채널 재매핑을 통한 단일 열화상 이미지 깊이 추정 향상)

  • Kim, Jeongyun;Jeon, Myung-Hwan;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.17 no.3
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    • pp.314-321
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    • 2022
  • Depth information used in SLAM and visual odometry is essential in robotics. Depth information often obtained from sensors or learned by networks. While learning-based methods have gained popularity, they are mostly limited to RGB images. However, the limitation of RGB images occurs in visually derailed environments. Thermal cameras are in the spotlight as a way to solve these problems. Unlike RGB images, thermal images reliably perceive the environment regardless of the illumination variance but show lacking contrast and texture. This low contrast in the thermal image prohibits an algorithm from effectively learning the underlying scene details. To tackle these challenges, we propose multi-channel remapping for contrast. Our method allows a learning-based depth prediction model to have an accurate depth prediction even in low light conditions. We validate the feasibility and show that our multi-channel remapping method outperforms the existing methods both visually and quantitatively over our dataset.