• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Journal of Pharmacopuncture
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• v.11 no.3
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• pp.113-122
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• 2008

Objective: The purpose of this study was to invigorate the use of infrared thermal imaging apparatus as a diagnostic tool in Oriental medicine by providing standard temperature on specific acupoints. Methods: Subjects for the study was recruited through an advertisement in the school homepage(www.sangji.ac.kr) explaining the objectives and methods. 100 volunteers agreeing to terms were selected and measured the full body thermal image. Common acupoints used in the clinical surrounding were chosen and final 63 acupoints were selected for the measurement. Male/female and right/left readings were obtained for the analysis. Results: Following results were obtained from analyzing the body temperature of 50 male subjects and 50 female subjects 1. Subjects participating in the study ranged from 19 years of age to 44 years. Median male age at $26.86{\pm}6.02$ and female age at $22.88{\pm}2.74$, respectively. 2. For all acupoints, no significant differences were witnessed between the gender and right, left side of the body. 3. 10 acupoints from the facial region(18 bilateral), 8 acupoints from the chest/abdomen region(10 bilateral), 6 acupoints from the back region(11 bilateral), 17 acupoints from the upper extremity(34 bilateral), and 22 acupoints from the lower extremity(44 bilateral) were chosen. 4. In the facial region, BL2 showed the highest temperature and GV26 showed the lowest. 5. In the chest/abdomen region, CV22 showed the highest temperature and CV6 showed the lowest. 6. In the back region, GV14 showed the highest temperature and BL23 showed the lowest. 7. In the upper extremity region, jianqian(extra point) showed the highest temperature and baxie(extra point) showed the lowest. 8. In the lower extremity region, KI1 and bafeng(extra point) shoed the highest temperature and BL40 showed the lowest. Conclusions: Based on the standard body temperature measured on specific acupoints throughout the body, we hope these findings can trigger further studies on applications of infrared thermal imaging and clinical usage in the field of oriental medicine.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.427-435
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• 2012

The aim of this study is to investigate facial temperature changes induced by facial expression and emotional state in order to recognize a persons emotion using facial thermal images. Background: Facial thermal images have two advantages compared to visual images. Firstly, facial temperature measured by thermal camera does not depend on skin color, darkness, and lighting condition. Secondly, facial thermal images are changed not only by facial expression but also emotional state. To our knowledge, there is no study to concurrently investigate these two sources of facial temperature changes. Method: 231 students participated in the experiment. Four kinds of stimuli inducing anger, fear, boredom, and neutral were presented to participants and the facial temperatures were measured by an infrared camera. Each stimulus consisted of baseline and emotion period. Baseline period lasted during 1min and emotion period 1~3min. In the data analysis, the temperature differences between the baseline and emotion state were analyzed. Eyes, mouth, and glabella were selected for facial expression features, and forehead, nose, cheeks were selected for emotional state features. Results: The temperatures of eyes, mouth, glanella, forehead, and nose area were significantly decreased during the emotional experience and the changes were significantly different by the kind of emotion. The result of linear discriminant analysis for emotion recognition showed that the correct classification percentage in four emotions was 62.7% when using both facial expression features and emotional state features. The accuracy was slightly but significantly decreased at 56.7% when using only facial expression features, and the accuracy was 40.2% when using only emotional state features. Conclusion: Facial expression features are essential in emotion recognition, but emotion state features are also important to classify the emotion. Application: The results of this study can be applied to human-computer interaction system in the work places or the automobiles.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.197-207
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• 2013

Difficulties of emissivity determination and atmospheric correction degrade the estimation accuracy of land surface temperature (LST). That is, since the emissivity determination of land surface material and the correction of atmospheric effect are not perfect, it is very difficult to estimate the precise LST from a thermal infrared image such as Landsat TM and ETM+, ASTER, etc. In this study, we propose an efficient method to estimate land surface temperature difference (LSTD) rather than LST from Landsat thermal band images. This method is based on the assumptions that 1) atmospheric effects are same over a image and 2) the emissivity of vegetation region is 0.99. To validate the performance of the proposed method, error sensitive analysis according to error variations of reference land surface temperature and the water vapor is performed. The results show that the estimated LSTD have respectively the errors of ${\pm}0.06K$, ${\pm}0.15K$ and ${\pm}0.30K$ when the water vapor error of ${\pm}0.302g/cm^2$ and the radiance differences of 0.2, 0.5 and $1.0Wm^{-2}sr^{-1}{\mu}m$ are considered. And also the errors of the LSTD estimation are respectively ${\pm}0.037K$, ${\pm}0.089K$, ${\pm}0.168K$ in the reference land surface temperature error of ${\pm}2.41K$. Therefore, the proposed method enables to estimate the LSTD with the accuracy of less than 0.5K.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.287-294
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• 2013

Purpose: Greenhouses for a protected horticulture covered with a plastic or glass are easy to have weakness in a heat loss by deterioration, damage, poor construction, and so on. To grasp the vulnerable points of heat loss of the greenhouses is important for heating energy saving. In this study, an on-site heat loss audit and energy consulting system were developed for an efficient energy usage of a greenhouse. Method: Developed system was mounted with infrared thermal and visual cameras to grasp the heat loss from the greenhouse quickly and exactly, and a trial calculation program of heating load of greenhouse to provide farmers with the information of heating energy usage. Results: Developed system could print out the reports about the locations and causes of the heat losses and improvement methods made up by an operator. The mounted trial calculation program could print out the information of the period heating load and fuel cost according to the conditions of greenhouse and cultivation. The program also mounted the databases of the information on the 13 horticultural energy saving technologies developed by the Korea Rural Development Administration and simple economic analysis sub-program to predict the payback period of the technologies. Conclusion: The developed system was expected to be used as the basic equipment for an instructors of district Agricultural Technology and Extension Centers to conduct the energy consulting service for the farmers within the jurisdiction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.53-61
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• 2012

This paper proposes a real-time distance measurement system of high temperature and high speed target using infrared stereo camera. We construct an infrared stereo camera system that measure the difference between target and background temperatures for automatic target measurement. First, the proposed method detects target region based on target motion and intensity variation of local region using difference between target and background temperatures. Second, stereo matching by left and right target information is used to estimate disparity about real-time distance of target. In the proposed method using infrared stereo camera system, we compare distances in three dimension trajectory measuring instrument and in infrared stereo camera measurement. In this experiment from three video data, the result shows an average 9.68% distance error rate. The proposed method is suitable for distance and position measurement of varied targets using infrared stereo system.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.111-116
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• 2012

Far-infrared observations provide crucial data for the investigation and characterisation of the properties of dusty material in the Interstellar Medium (ISM), since most of its energy is emitted between ~ 100 and $200{\mu}m$. We present the first all-sky image from a sensitive all-sky survey using the Japanese AKARI satellite, in the wavelength range $50-180{\mu}m$. Covering > 99% of the sky in four photometric bands with four filters centred at $65{\mu}m$, $90{\mu}m$, $140{\mu}m$, and $160{\mu}m$ wavelengths, this achieved spatial resolutions from 1 to 2 arcmin and a detection limit of < 10 MJy $sr^{-1}$, with absolute and relative photometric accuracies of < 20%. All-sky images of the Galactic dust continuum emission enable astronomers to map the large-scale distribution of the diffuse ISM cirrus, to study its thermal dust temperature, emissivity and column density, and to measure the interaction of the Galactic radiation field and embedded objects with the surrounding ISM. In addition to the point source population of stars, protostars, star-forming regions, and galaxies, the high Galactic latitude sky is shown to be covered with a diffuse filamentary-web of dusty emission that traces the potential sites of high latitude star formation. We show that the temperature of dust particles in thermal equilibrium with the ambient interstellar radiation field can be estimated by using $90{\mu}m$, $140{\mu}m$, and $160{\mu}m$ data. The FIR AKARI full-sky maps provide a rich new data set within which astronomers can investigate the distribution of interstellar matter throughout our Galaxy, and beyond.

• Journal of Bio-Environment Control
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• v.25 no.4
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• pp.302-307
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• 2016

The aim of this study was to examine the optimum wattage and installation height using nano-carbon fiber infrared heating lamp (NCFIHL) for heating energy saving and plug seedling production in plug seedling production greenhouse in winter season. NCFIHL of 700 and 900 W was installed over the bed ($1.2{\times}2.4m$) as 0.7, 1.0, and 1.3 m height, respectively, for the production of grafted watermelon seedling in venlo-type glasshouse. Watermelon (Citrullus lanatus (Thunb.) Manst.) 'Jijonggul' and gourd (Lagenaria leucantha Rusby.) 'Sunbongjang' were used as scions and rootstocks, respectively. The scions and rootstocks were grafted by single cotyledon ordinary splice grafting. Light intensity of NCFIHL was below the $1{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ in all treatment. Spectral distributions of NCFIHL presented mostly infrared area. When outside air temperature was below $10^{\circ}C$, 700 and 900 W NCFIHL installed with 0.7 m height treatment and 900 W NCFIHL installed with 1.0 m height treatment maintained the setting air temperature ($20^{\circ}C$) at night. In the result of taking thermal imaging, the grafted watermelons were getting warm fast in 900 W NCFIHL installed with 0.7 m height treatment at night. Compactness of the grafted watermelons was the greatest in 700 W NCFIHL installed with 1.3 m height treatment. The results indicate that NCFIHL installed above 1.0 m height using 700 W was suitable for production of plug seedling.