• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.6
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• pp.665-670
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• 2011

In this paper, a new approach to detect surface cracks from a noisy thermal image in the infrared thermography is presented using an holomorphic characteristic of temperature field in a thin plate under steady-state thermal condition. The holomorphic function for 2-D heat flow field in the plate was derived from Cauchy Riemann conditions to define a contour integral that varies according to the existence and strength of a singularity in the domain of integration. The contour integral at each point of thermal image eliminated the temperature variation due to heat conduction and suppressed the noise, so that its image emphasized and highlighted the singularity such as crack. This feature of holomorphic function was also investigated numerically using a simple thermal field in the thin plate satisfying the Laplace equation. The simulation results showed that the integral image selected and detected the crack embedded artificially in the plate very well in a noisy environment.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.33-37
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• 2011

This paper presents the frequency spectral analysis based on FFT of the infrared ray fire thermal image, it is an object to deduce the conditions for determining fire alarm through the image processing with the frequency domain. After the candidate regions are separated by using pre-defined brightness value, the fast fourier transform is performed for consecutive infrared thermal images, the frequency spectral analysis of the thermal image analyzed DC and AC frequency distribution. The fire criterion of the thermal image was presented based on the analyzed result and a practicality was confirmed through the computer simulation.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.6
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• pp.398-406
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• 2015

This paper explored the results of experimental investigation on carbon fiber reinforced polymer (CFRP) composite sample with thermal wave technique. The thermal wave technique combines the advantages of both conventional thermal wave measurement and thermography using a commercial Infrared camera. The sample comprises the artificial inclusions of foreign material to simulate defects of different shape and size at different depths. Lock-in thermography is employed for the detection of defects. The temperature field of the front surface of sample was observed and analysed at several excitation frequencies ranging from 0.562 Hz down to 0.032 Hz. Four-point methodology was applied to extract the amplitude and phase of thermal wave's harmonic component. The phase images are analyzed to find qualitative and quantitative information about the defects.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.260-270
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• 2023

We introduce a novel Visual Inertial Odometry (VIO) algorithm designed to improve the performance of thermal-inertial odometry. Thermal infrared image, though advantageous for feature extraction in low-light conditions, typically suffers from a high noise level and significant information loss during the 8-bit conversion. Our algorithm overcomes these limitations by approximating a 14-bit raw pixel histogram into a Gaussian mixture model. The conversion method effectively emphasizes image regions where texture for visual tracking is abundant while reduces unnecessary background information. We incorporate the robust learning-based feature extraction and matching methods, SuperPoint and SuperGlue, and zero velocity detection module to further reduce the uncertainty of visual odometry. Tested across various datasets, the proposed algorithm shows improved performance compared to other state-of-the-art VIO algorithms, paving the way for robust thermal-inertial odometry.

• Journal of Technologic Dentistry
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• v.36 no.3
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• pp.141-147
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• 2014

Purpose: Dental casting #Gr I (Co-25Cr-5Mo-3Sn-1Mn-1Si), #Gr II (Co-25Cr-5Mo-5Cu-1Mn -1Si) and #Gr III (Co-25Cr-5Mo-3Sn-5Cu-1Mn-1Si) master alloys of granule type were manufactured the same as manufacturing processes for dental casting Ni-Cr and Co-Cr-Mo based alloys of ingot type. These alloys were analyzed melting processes with heating time of high frequency induction centrifugal casting machine using infrared thermal image analyzer. Methods: These alloys were manufactured such as; alloy design, the first master alloy manufatured using vacuum arc casting machine, melting metal setting in crucible, melting in VIM, pouring in the mold of bar type, cutting the gate and runner bar and polishing. These alloys were put about 30g/charge in the ceramic crucible of high frequency induction centrifugal casting machine and heat, Infrared thermal image analyzer indicated alloys in the crucible were set and operated. Results: The melting temperatures of these alloys measuring infrared thermal image analyzer were decreased in comparison with remanium$^{(R)}$ GM 800+, vera PDI$^{TM}$, Biosil$^{(R)}$ f, WISIL$^{(R)}$ M type V, Ticonium 2000 alloys of ingot type and vera PDS$^{TM}$(Aabadent, USA), Regalloy alloys of shot type. Conclusion: Co-Cr-Mo based alloy in addition to Sn(#Gr I alloy) were decreased the melting temperature with heating time of high frequency induction centrifugal casting machine using infrared thermal image analyzer.

• Convergence Security Journal
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• v.22 no.2
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• pp.21-26
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• 2022

Wearing face masks is an effective measure to prevent COVID-19 infection. Infrared thermal image based temperature measurement and identity recognition system has been widely used in many large enterprises and universities in China, so it is totally necessary to research the face mask detection of thermal infrared imaging. Recently introduced MTCNN (Multi-task Cascaded Convolutional Networks)presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask MTCNN is an algorithm that extends MTCNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. It is easy to generalize the R-CNN to other tasks. In this paper, we proposed an infrared image detection algorithm based on R-CNN and detect heating elements which can not be distinguished by RGB images.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.128-132
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• 2007

Thermal Imaging systems are reported to be crucial for fire fighting and beginning to be used by fire fighters. The performance of thermal imaging system is determined by both the radiation of infrared from the target and the attenuation of infrared signal in the optical path by the absorption, scattering, diffraction and reflection. In the scene of fire, water drops with various sizes such as vaporized water, wafer mist from sprinkler, and wafer to suppress the fire reside with various gas generated by burning. To measure the transmission of infrared radiation in the scene of fire, fire simulating system and thermal imagers with cooled detector which detects $3{\sim}5{\mu}m$ infrared and uncooled detector fabricated by the MEMS technology which detects $8{\sim}12{\mu}m$ infrared. are made. With thermal imagers and Ire simulating system, the change of thermal image with respect to the change of visibility controlled with the burned fas was measured. It was found that the transmission of infrared was not reduced by the burned gas, which could be explained by the long wavelength of infrared ray compared with visible ray. However, the transmission of infrared ray was largely reduced by the combination of burned gas and water mist supplied by sprinkler. This is contrary to the results of calculated transmission through the pure water mist and shows that the transmission of infrared ray is mostly affected by the compounds of water mist and burned gas. In this case, it was found that the uncooled detector which detects $8{\sim}12{\mu}m$ infrared ray is better than cooled detector which detects $3{\sim}5{\mu}m$ infrared ray for fire fighting.

• Journal of IKEEE
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• v.22 no.3
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• pp.578-584
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• 2018

Image segmentation has been presented in the various method in image interpretation and recognition, and the image is using separate the characteristics of the specific purpose. In this paper, we proposed an algorithm that separate image for feature points detected to high temperature in a Thermal infrared image. In order to improve the processing time, the proposed algorithm is implemented to FPGA Hardware Block using the Zynq-7000 Evaluation Board environment. The proposed High-Temperature Detection Algorithm and total FPGA blocks show a decrease of a processing time result from 16ms to 0.001ms, and from 50ms to 0.322ms respectively. It is also verified similar results of the PSNR to comparing software thermal testbench and hardware ones.

• 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.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.280-293
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• 2018

The conversion of an invisible thermal radiation pattern of an object into a visible image using infrared (IR) thermal technology is very useful to understand phenomena what we are interested in. Although IR thermal images were originally developed for military and space applications, they are currently employed to determine thermal properties and heat features in various applications, such as the non-destructive evaluation of industrial equipment, power plants, electricity, military or drive-assisted night vision, and medical applications to monitor heat generation or loss. Recently, IR imaging-based monitoring systems have been considered for application in agricultural, including crop care, plant-disease detection, bruise detection of fruits, and the evaluation of fruit maturity. This paper reviews recent progress in the development of IR thermal imaging techniques and suggests possible applications of thermal imaging techniques in agriculture.