• Title/Summary/Keyword: IR thermal image

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Multi-Level Segmentation of Infrared Images with Region of Interest Extraction

  • Yeom, Seokwon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.246-253
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    • 2016
  • Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

Automatic Registration Method for EO/IR Satellite Image Using Modified SIFT and Block-Processing (Modified SIFT와 블록프로세싱을 이용한 적외선과 광학 위성영상의 자동정합기법)

  • Lee, Kang-Hoon;Choi, Tae-Sun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.3
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    • pp.174-181
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    • 2011
  • A new registration method for IR image and EO image is proposed in this paper. IR sensor is applicable to many area because it absorbs thermal radiation energy unlike EO sensor does. However, IR sensor has difficulty to extract and match features due to low contrast compared to EO image. In order to register both images, we used modified SIFT(Scale Invariant Feature Transform) and block processing to increase feature distinctiveness. To remove outlier, we applied RANSAC(RANdom SAample Concensus) for each block. Finally, we unified matching features into single coordinate system and remove outlier again. We used 3~5um range IR image, and our experiment result showed good robustness in registration with IR image.

Performance Analysis of Object Detection Neural Network According to Compression Ratio of RGB and IR Images (RGB와 IR 영상의 압축률에 따른 객체 탐지 신경망 성능 분석)

  • Lee, Yegi;Kim, Shin;Lim, Hanshin;Lee, Hee Kyung;Choo, Hyon-Gon;Seo, Jeongil;Yoon, Kyoungro
    • Journal of Broadcast Engineering
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    • v.26 no.2
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    • pp.155-166
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    • 2021
  • Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.

Analysis of infrared thermal image for melting processes of Co-Cr-Mo based alloy using high frequency induction casting machine (치과용 고주파 주조기를 이용한 Co-Cr-Mo계 합금 용해과정의 적외선 열화상 분석)

  • Kang, Hoo-Won;Park, Young-Sik;Hwang, In;Lee, Chang-Ho;Heo, Yong;Won, Yong-Gwan
    • Journal of Technologic Dentistry
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    • v.36 no.3
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    • pp.149-158
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    • 2014
  • Purpose: Dental casting Co-Cr-Mo based alloys of five kinds of ingot type and two kinds of shot type were analyzed the melting processes with heating time of high frequency induction centrifugal casting machine using infrared thermal image analyzer. Methods: When Co-Cr-Mo based alloys were put about 30g/charge in the ceramic crucible of high frequency induction centrifugal casting machine and heat, Infrared thermal image analyzer and IR thermometer indicated these alloys in the crucible were set and operated. Results: The melting temperatures of alloys measuring infrared thermal image analyzer were deviated ${\pm}10^{\circ}C$ compared to those of manufacturing company. On the other hand, the melting time of alloys were differently appeared with the shape of alloys(ingot and shot type). Conclusion: The melting temperatures of dental Co-Cr-Mo based alloys were measured the degree of $1,360{\sim}1410^{\circ}C$ and the heating time with the alloys of ingot and shot type were deviated ${\pm}10sec$.

IR signature modeling using an equivalent thermal circuit (등가 열회로를 이용한 물체의 적외선 특성 모델링)

  • 홍현기;한성현;홍경표;최종수
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.1
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    • pp.122-129
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    • 1998
  • For generation and analysis of the multi-sensory image, we propose a new three dimensional (3D) modeling method considering an iternal heat source. We represent the heat conduction process within th object as an equivalent thermal circuit. Therefore, without a complex computation, our modeling approach can obtain thermal features of the object. By using the faceted model, the proposed method can express the accurate visual signatures of the object. Comparing the estimates datum with the obtained surface temperatures, we have demonstrated that the proposed method can provide a precise thermal features. The thermal images by out model is applicable to simulate a tracking loop of an IR missile.

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Variation of Carbonization Pattern and Crystal Structure of Polyvinyl Chloride Wire Under the Thermal Stresses (열 스트레스에 의한 비닐절연전선의 탄화 패턴 및 결정 구조의 변화)

  • Choi, Chung-Seog;Kim, Hyang-Kon
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.57 no.3
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    • pp.332-337
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    • 2008
  • We analyzed carbonization pattern and crystal structure of polyvinyl chloride wire by thermal stress. Copper that is oxidized at normal temperature is a reddish brown. If under the thermal stress range of 500 to 700 [$^{\circ}C$], carbonization and exfoliation occurrence. Section structure of electric wire is same as arrangement of particle in metallograph analysis. But, as thermal stress increases, size of particle is enlarged. Electric wire displays elongation structure in SEM image analysis and elongation structure collapses when receive thermal stress at 300 [$^{\circ}C$]. In EDX analysis, we get the spectra of CuL, CuK, OK, and ClK. FT-IR analysis was shown new spectra with in range of $1,440{\sim}1,430\;[cm^{-1}]$, 1,340 [$cm^{-1}$], 1,240 [$cm^{-1}$].

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.493-505
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    • 2023
  • Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

Development of Interferometer for Performance Assessment of IR Optical System (적외선 광학계통 성능평가를 위한 간섭계 개발)

  • 홍경희;고재준;이성태;장세안;오명호
    • Korean Journal of Optics and Photonics
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    • v.2 no.4
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    • pp.179-185
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    • 1991
  • Twyman-Green interferometer is developed for assessment of IR optical system performance. Light source is $CO_2$ gas laser which has 10.6$\mu \textrm m$ wavelength. The light beam is expanded to 2.5 cm dia by Ge lens and splitted by ZnSe parallel plane plate. One of the beams is reflected by refernce mirror which is operated PZT. The fringe will be detected by a pyro-electric vidicon camera and displayed by a CRT monitor. Here, the IR firinge is recorded on the thermal paper. In visible region, the light source is He-Ne laser. The fringe is detected by a CCD camera and displayed by the CRT monitor. The intensity of the fringe is digitized by a image card and processed by a PC. The wavefront aberration function, PSF and OTF are calculated. The results are displayed in 3-D graphs on the monitor or printed out by a line printer.

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Performance Evaluation of Image Saturation of Thermal Imaging Camera for the Fire Service (화재용 열화상 카메라의 영상포화특성 평가)

  • Kim, Sung-Chan
    • Fire Science and Engineering
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    • v.26 no.2
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    • pp.69-74
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    • 2012
  • Thermal imaging technology based on IR sensor with high transmittance through the fire smoke is considered as one of the advanced technology for the fire service. The present study has been performed to investigate the image saturation characteristics with thermal condition of target and background and evaluate the performance of image quality based on the contrast transfer function (CTF). For the present testing conditions, TIC using BST sensor did not show the image saturation and the image quality based on the CTF was proportional to the temperature difference between target and background. This study can be utilized as preliminary study to improve reliability and technical development of TIC.

The design methods of Infrared Camera with Continuous zoom

  • Son, Seok-Hyeon
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.12
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    • pp.19-26
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    • 2016
  • In this paper, we propose an efficient design method for a thermal camera with continuous zoom based on the research and manufacturing experience of the thermal camera. In addition, it is divided into system design method, optical design method, mechanical design method, and electronic design method. First, we propose an effective NUC compensation method and a lens-specific sensitivity design method in terms of system. Second, we propose a zoom trajectory design method considering the temperature effect on the optical aspect. Third, it suggests the minimization of optical axis shaking between magnification conversion in terms of mechanism. Finally, we propose a lens-specific temperature compensation method and a speed conversion algorithm according to the zoom interval as an electronic aspect.