Thermal Imaging Camera Research Articles

Comparison of two 3D calibration methods for thermal imaging cameras to track bat flight paths near wind turbines

Zusammenfassung 3D Kameras mit geringer Auflösung, die in einem großen Außenvolumen eingesetzt werden sollen, benötigen große interaxiale Abstände von einigen Metern zwischen den Kameras. Das ist zum Beispiel der Fall, wenn 3D Fledermaus- Flugbahnen mit Wärmebildkameras in der Nähe von Windenergieanlagen erforscht werden, um deren Auswirkungen auf die Tiere zu untersuchen. Derartige Kamera- Systeme müssen nach erfolgter Montage der Kameras im Feld 3D kalibriert werden. Dazu haben wir zwei Methoden identifiziert, die große interaxiale Abstände ermöglichen: Eine Methode (easyWand) basiert auf Landmarken die in beiden Kameras sichtbar sind und eine weitere von uns entwickelte Methode (Batflight3D) basiert auf dem 3D Flugpfad einer Drohne. In dieser Publikation versuchen wir einen möglichst repräsentativen quantitativen Vergleich dieser Methoden, indem wir die 2D Korrespondenzen des jeweiligen Drohnenflugpfades für beide Methoden nutzen, um sie so direkt miteinander vergleichen zu können. Die Ergebnisse zeigen, dass Batflight3D für den oben genannten Anwendungsfall wesentlich genauere und auch verlässlichere Ergebnisse liefert, aber auf die Möglichkeit eines Drohnenfluges und GPS-Empfangs angewiesen ist.

Thermal Image Based Occupant Count Measurement Model using Human Body Temperature for Smart Building

Objectives: The proposed Occupant Count Measurement (OCM) model aims to enhance sustainability, energy efficiency, comfort, and safety in smart buildings by accurately determining occupant count using thermal camera images and body temperature data. Methods: The model leverages real-time thermal camera images without the need for a pre-existing dataset. Key parameters include temperature threshold, occupant motion, size, and shape to ensure accurate occupancy estimation. The K-means algorithm identifies and clusters regions of interest (ROI) in thermal images corresponding to human body temperatures. The model also employs sensors like PIR, RGB cameras, and thermal image sensors. Manual counting serves as a benchmark for comparison. Findings: The K-means algorithm extracts regions with elevated temperatures related to human bodies from thermal images, partitioning them into K-clusters based on temperature ranges and assigning each pixel to one of the clusters. A temperature threshold differentiates human clusters in the thermal image, while connected component labeling refines human object segmentation by identifying blobs, which are then used for occupant counting. The model's precision is assessed using diverse image sensors and compared to the actual number of occupants. The proposed OCM model achieves an accuracy of about 90.2% compared to traditional methods. Novelty: This study introduces an OCM model that uses thermal images to estimate the number of occupants in a room based on their body temperature. The method focuses on detecting and counting occupants by their overall thermal body signature, providing a novel approach to occupant measurement in smart buildings. Keywords: Thermal Images, Segmentation, Occupant Estimation, Occupant Comfort, Smart Building

Evaluating Daily Water Stress Index (DWSI) Using Thermal Imaging of Neem Tree Canopies under Bare Soil and Mulching Conditions

Water stress on crops can severely disrupt crop growth and reduce yields, requiring the accurate and prompt diagnosis of crop water stress, especially in semiarid regions. Infrared thermal imaging cameras are effective tools to monitor the spatial distribution of canopy temperature (Tc), which is the basis of the daily water stress index (DWSI) calculation. This research aimed to evaluate the variability of plant water stress under different soil cover conditions through geostatistical techniques, using detailed thermographic images of Neem canopies in the Brazilian northeastern semiarid region. Two experimental plots were established with Neem cropped under mulch and bare soil conditions. Thermal images of the leaves were taken with a portable thermographic camera and processed using Python language and the OpenCV database. The application of the geostatistical technique enabled stress indicator mapping at the leaf scale, with the spherical and exponential models providing the best fit for both soil cover conditions. The results showed that the highest levels of water stress were observed during the months with the highest air temperatures and no rainfall, especially at the apex of the leaf and close to the central veins, due to a negative water balance. Even under extreme drought conditions, mulching reduced Neem physiological water stress, leading to lower plant water stress, associated with a higher soil moisture content and a negative skewness of temperature distribution. Regarding the mapping of the stress index, the sequential Gaussian simulation method reduced the temperature uncertainty and the variation on the leaf surface. Our findings highlight that mapping the Water Stress Index offers a robust framework to precisely detect stress for agricultural management, as well as soil cover management in semiarid regions. These findings underscore the impact of meteorological and planting conditions on leaf temperature and baseline water stress, which can be valuable for regional water resource managers in diagnosing crop water status more accurately.

Pencil-drawn tunable electrical resistance and Joule heating demonstration using a smartphone-based thermal imaging camera

This paper delves into the educational potential of pencil circuits for teaching key electrical concepts. Using both practical experiments and theoretical examinations, this study explores the application of pencil circuits in demonstrating concepts related to series and parallel resistance, Ohm’s law, and Joule’s heating law. By leveraging the simplicity and accessibility of pencil-based setups, students can gain a practical understanding of these fundamental principles. Additionally, the integration of thermal imaging technology enhances the visualization of Joule’s heating law, further enriching the learning experience.

Predicting Blooming Day of Cut Lily through Wavelength Reflectance Analysis

Domestic export cut lily flowers are expensive in Japan when they are in bud state that has not yet bloomed and when no leaf yellowing has occurred. Predicting the blooming day of domestic cut lily flowers is essential to increase their commodity value. Thermal imaging, spectroscopic technologies, and hyperspectral cameras have recently been used for quality prediction. This study uses a hyperspectral camera, reflectance of wavelength, and a support vector machine (SVM) to evaluate the predictability of blooming days of cut lily flowers. While examining spectra at wavelengths of 750–900 nm associated with pollination, the resultant reflectance was over 75% during six to four days before blooming and 30% on a blooming day, indicating a decline in their reflectance toward blooming. Furthermore, SVM classification models based on kernel function revealed that the quadratic SVM had the highest accuracy at 84.4%, while the coarse Gaussian SVM had the lowest accuracy at 34.4%. The most crucial wavelength for the quadratic SVM was 842.3 nm, which was associated with water. The quadratic SVM’s accuracy, verified using the area under the curve (ACU), was above 0.8, showing suitability for spectral classification based on blooming day prediction. Thus, this study shows that hyperspectral imaging can classify spectra based on the blooming day, indicating its potential to predict the blooming day, vase life, and quality of cut lily flowers.

Broadband achromatic thermal metalens with a wide field of view based on wafer-level monolithic processes

We present a monolithic metalens free of chromatic aberration over the 8–12 μm wavelength range for thermal imaging. The metalens consists of nano-donut-pillars for dispersion engineering. The proposed metalens design is based on a telecentric optical system, which effectively eliminates off-focus distortion and aberration, enhancing overall imaging quality. Offering a 90° field of view, the metalens ensures uniform focal spot sizes within a 45° field angle across the working wavelength. This enables the capture of high-quality thermal images with sharp images and minimal distortion. With a diameter of 5.75 mm, the metalens is suitable for integration into commercial thermal imaging cameras. The nano-donut-pillar structure of the metalens allows for relatively straightforward mass production, involving i-line stepper lithography and silicon deep etching processes.

What not to do in facial infrared thermographic measurements: A post data enhancement

The accuracy of infrared thermographic measurements depends on several factors, including movement of target. In this study, accuracy of nose tip temperatures obtained in a mental workload assessment using a thermal imaging camera were impacted by participants’ movement and camera zooming/panning. To correct these measurement errors, we compared manual facial landmark identification techniques using data labelling software with an automated deep learning-based approach utilised for facial landmark tracking and evaluated both against the built-in tracking features of the thermal camera, Thermal Spot Tracking. Using the Manual Thermal Landmark Annotation measurements as the ground truth, our results show that the Automated Facial Feature Tracking approach, which is the AI based approach performed better than the Thermal Spot Tracking as it matched comparatively more spatial coordinates and temperature datapoints as well as showed comparatively lower mean relative error. The study highlights the potential of AI in enhancing the accuracy of thermographic measurements, particularly in applications involving facial temperature analysis.

Mathematical Modeling of the Heat Transfer Process in Spherical Objects with Flat, Cylindrical and Spherical Defects

This paper proposes a method for determining the optimal parameters for the thermal testing of plant tissues of fruits and vegetables containing surface and subsurface defects in the form of areas of plant tissues with different thermophysical characteristics. Based on well-known mathematical models for objects of predominantly flat, cylindrical and spherical shapes containing flat, spherical and cylindrical regions of defects, numerical solutions of three-dimensional, non-stationary temperature fields were found, making it possible to measure the power and time of the thermal exposure of the sample surface to the radiation from infrared lamps using the finite element method. This made it possible to ensure the reliable detection of a temperature contrast of up to 4 °C between the defect and defect-free regions of the test object using modern thermal imaging cameras. In this case, subsurface defects can be detected at a depth of up to 3 mm from the surface. To determine the parameters of mathematical models of temperature fields, such as thermal conductivity and a coefficient of the thermal diffusivity of plant tissues, a new method of a pulsed heat flux from a flat heater is proposed; this differs in the method of processing experimental data and makes it possible to determine the required characteristics with high accuracy during the active stage of the experiment in a period not exceeding 1–3 min.

Experimental Study to Visualize a Methane Leak of 0.25 mL/min by Direct Absorption Spectroscopy and Mid-Infrared Imaging

Tunable laser spectroscopy (TLS) with infrared (IR) imaging is a powerful tool for gas leak detection. This study focuses on direct absorption spectroscopy (DAS) that utilizes wavelength modulation to extract gas information. A tunable interband cascade laser (ICL) with an optical power of 5 mW is periodically modulated by a sawtooth injection current at 10 Hz across the methane absorption around 3271 nm. A fast and sensitive thermal imaging camera for the mid-infrared range between 3 and 5.7 µm is operated at a frame rate of 470 Hz. Offline processing of image stacks is performed using different algorithms (DAS-F, DAS-f and DAS-2f) based on the Lambert–Beer law and the HITRAN database. These algorithms analyze various features of gas absorption, such as area (F), peak (f) and second derivative (2f) of the absorbance. The methane concentration in ppm*m is determined on a pixel-by-pixel analysis without calibration. Leak localization for methane leak rates as low as 0.25 mL/min is accurately displayed in a single concentration image with pixelwise sensitivities of approximately 1 ppm*m in a laboratory environment. Concentration image sequences represent the spatiotemporal dynamics of a gas plume with high contrast. The DAS-2f concept demonstrates promising characteristics, including accuracy, precision, 1/f noise rejection, simplicity and computational efficiency, expanding the applications of DAS.

An Experimental and Clinical Study of Flap Monitoring with an Analysis of the Clinical Course of the Flap Using an Infrared Thermal Camera.

Flap surgery is a common method used to cover defects following tumor ablation, trauma, or infection. However, insufficient vascularity in the transferred flap can lead to flap necrosis and failure. Proper postoperative monitoring is essential to prevent these complications. Recently, research has explored the use of infrared thermal imaging in plastic surgery, leading to its clinical application. This study comprises two separate parts: an in vivo experimental study and a clinical study. In this study, 28 rats underwent reverse McFarlane flap surgery, and their flaps were analyzed using a FLIR thermal imaging camera seven days post-surgery. Additionally, thermal images of flaps were taken on postoperative days 0, 1, 2, 3, and 7 in 22 patients. This study focused on temperature differences between normal skin and the perforator compared to the average flap temperature. Results showed that the temperature difference was higher in the necrosis group and increased over time in cases of total necrosis. A lower perforator temperature compared to the flap's average indicated vascular compromise, potentially leading to flap failure. The FLIR camera, being contact-free and convenient, shows promise for understanding and inferring the clinical progression of flaps in postoperative monitoring.

Lantern-like hollow nanoparticles with high-efficiency photothermal property for the point-of-care detection of illegal additive

The detection of illegal additives in food or health products is of importance, as the excessive consumption of such products has detrimental effects on human health. Surface-enhanced Raman spectroscopy and liquid chromatograph-tandem mass spectrometry are widely employed for the detection of hazardous substances in food, however, their applicability for point-of-care test (POCT) is limited. In this work, a novel photothermal material, PdCu@Cu2O, was synthesized using polyhedron Cu2O as template and then doping with Pd nanoparticles by in-situ reduction. PdCu@Cu2O had a lantern-like hollow nanocage morphology with a core-shell structure that improved the refractive index of incident light, while the symmetric structure facilitated the strong absorption resonance, thus PdCu@Cu2O exhibited a high photothermal conversion efficiency of 46.4 %. Finally, a photothermal immunosensor was developed for the sensitive detection of aminopyrine in a range of 5×10−5-1×10−1 μg/mL, which can realize facile photothermal recognition using a miniaturized near-infrared lamp and handheld thermal imaging device. This portable device can easily transform the temperature signal to achieve target concentration, thus providing an effective way to visualize POCT detection in resource-limited areas.

Algorithm for measuring parameters of radio link of an unmanned aircraft in fpv mode of the centimeter frequency range

The mass use of unmanned aerial vehicles (UAVs) in the mode of remote control "from the first person" (First Person View, FPV) in combat operations radically changes the picture of modern war. Their use makes it possible to damage or destroy enemy equipment, the cost of which is hundreds of times higher than the cost of UAVs. To successfully perform the UAV flight mission in FPV mode, it is necessary to ensure stable radio communication of the UAV with the ground control station (GSC). In the work to organize a radio line between the GSC and the UAV, it is proposed to use radio lines of the centimeter frequency range. At the same time, at the stage of flight mission planning, the UAV operator needs to have information about the parameters of the receiving and transmitting devices of the unmanned aerial vehicle complex (UAVС) in order to calculate the maximum flight range. The purpose of the work is to develop an algorithm for measuring parameters of the radio link of an unmanned aerial vehicle in the FPV mode of the centimeter frequency range. The use of this information will allow the UAVC operator to create a flight map and prepare for a combat mission. The material presented in the article contains practical value for UAV operators and can be used in the organization and planning of the flight mission of multi-rotor UAVs of the tactical level at a given distance. Also, the material can be used by UAV service units for the purpose of checking the technical parameters of the radio link between the UAV and GSC and the optical systems installed on board the UAV (video cameras, thermal imaging cameras, etc.).

Lizard Body Temperature Acquisition and Lizard Recognition Using Artificial Intelligence.

The acquisition of the body temperature of animals kept in captivity in biology laboratories is crucial for several studies in the field of animal biology. Traditionally, the acquisition process was carried out manually, which does not guarantee much accuracy or consistency in the acquired data and was painful for the animal. The process was then switched to a semi-manual process using a thermal camera, but it still involved manually clicking on each part of the animal's body every 20 s of the video to obtain temperature values, making it a time-consuming, non-automatic, and difficult process. This project aims to automate this acquisition process through the automatic recognition of parts of a lizard's body, reading the temperature in these parts based on a video taken with two cameras simultaneously: an RGB camera and a thermal camera. The first camera detects the location of the lizard's various body parts using artificial intelligence techniques, and the second camera allows reading of the respective temperature of each part. Due to the lack of lizard datasets, either in the biology laboratory or online, a dataset had to be created from scratch, containing the identification of the lizard and six of its body parts. YOLOv5 was used to detect the lizard and its body parts in RGB images, achieving a precision of 90.00% and a recall of 98.80%. After initial calibration, the RGB and thermal camera images are properly localised, making it possible to know the lizard's position, even when the lizard is at the same temperature as its surrounding environment, through a coordinate conversion from the RGB image to the thermal image. The thermal image has a colour temperature scale with the respective maximum and minimum temperature values, which is used to read each pixel of the thermal image, thus allowing the correct temperature to be read in each part of the lizard.

Experimental Measurement of Emissivity of Polished Steel Strips from a Continuous Annealing Line.

The long-term use of steel strip in various industries makes it an important semi-finished product, which makes it necessary to improve its chemical composition and mechanical properties, reduce its thickness and weight, expand the range of new types of steel strip and increase its production. This entails a large number of technological operations dependent on precise temperature measurement and control. In some industrial plants, the steel strip is in continuous motion, which makes the use of contact measuring devices impossible. When using non-contact measuring devices such as pyrometers or thermal imaging cameras, the emissivity of the materials being measured is a problematic parameter, as setting an incorrect emissivity value to the measuring device results in inaccurate temperature readings. The essence of this research was to establish a measurement method and to perform experimental measurements of the emissivity of a polished steel strip used in a continuous annealing line, the subsequent processing of the data from these measurements and their evaluation. The emissivity measurements were carried out for 5 types of steel strip of different parameters, while the measurement itself was carried out in the long wavelength range of 7.5-14 µm and at strip temperatures of 100-300 °C. Depending on the type of steel strip, the mean emissivity values ranged from 0.0835- to 0.1143. The emissivity of the steel strip increased with increasing strip temperature, and it was not a linear dependence. The emissivity values determined in this research could be applied to measuring equipment in actual production, which could improve the accuracy of temperature measurement in the heat treatment of polished steel strip. Thermal camera measurements in the long wavelength range, taking thermal images and their processing and determining the emissivity value of polished steel strips are the parts of this research that make it different from other already published research.

The research on infrared radiation affected by smoke or fog in different environmental temperatures

Infrared thermal imaging camera as a non-contact monitoring of the object to be measured is widely used in fire detection, driving assistance and so on. Although there are many related studies, there is a lack of research on the influence of fog or smoke on infrared imaging under different environmental temperatures. To address this shortcoming, The temperature of both the environment and the target in this experiment is controlled by PID technology. The smoke or fog environment is generated using a smoke cake or an ultrasonic fog machine. The temperature of the target was measured by infrared thermal imaging camera. It was observed that as the temperature of the environment increases, the measured temperature of the target also increases. However, the change in temperature is more pronounced in the fog environment compared to either the smoke environment or the normal environment. It has been found through research that environmental radiation causes temperature changes in fog droplets. Therefore, Infrared radiation is less affected in the smoke environment and more affected in the fog environment. Additionally, when the environmental temperature is close to the target's temperature, the infrared image becomes blurred.

Tightly coupled visual-inertial fusion with image enhancement for robust positioning

Abstract Traditional vision-based inertial odometry (VIO) suffers from significant visual degradation, which substantially impacts state estimation in challenging lighting environments. Thermal imaging cameras capture images based on the thermal radiation of objects, rendering them impervious to lighting variations. However, integrating thermal infrared data into conventional visual odometry poses challenges due to its low texture, poor contrast, and high noise levels. In this paper, we propose a tightly coupled approach that seamlessly integrates information from visible light cameras, thermal imaging cameras, and inertial measurement units (IMUs). First, we employ adaptive bilateral filtering and Sobel gradient enhancement to smooth infrared images, thereby reducing noise and enhancing edge contrast. Second, we leverage the Sage-Husa adaptive filter in conjunction with iterative Kalman filtering (IEKF) to effectively mitigate the impact of non-Gaussian noise on the system. Finally, we conduct comprehensive evaluations of the proposed system using both open datasets and real-world experiments across four distinct scenarios: normal lighting, low-light conditions, low-light conditions with camera shake, and challenging lighting environments. Comparative analysis reveals that our method outperforms IEKF, yielding a reduction in localization error measured by root mean square error (RMSE) by 58.69%, 57.24%, 60.23%, and 30.87% in these respective scenarios.

Experimental assessment of the effect of reflectors on the thermal behavior of box-type solar furnaces

Solar ovens are eco-friendly ovens that use solar energy, a clean, sustainable and above all free source of energy. In the context of the economic and environmental crises facing the world today, solar cookers are considered a good alternative to electric cookers or those based on wood combustion. Several types of solar cooker have been developed in recent years. However, the box type remains the most efficient and simplest. To this end, an experimental study of three types of box-type solar cookers (triangle, trapezoid and rectangle) was carried out in this work. For each type of solar cooker, the effect of the number of reflectors added to the Cookers system was examined. The experimental tests were carried out in August 2023 under the climatic conditions of Morocco's eastern region. The evaluation of the systems studied is based on the hourly evolution of air, absorber and load temperatures for each type of solar furnace in different cases. Thermal photos were also taken using a Dia-Cam thermal imaging camera to visualize temperature distribution and analyze the thermal behavior of the systems. The obtained results show that the thermal behavior of three solar furnaces and the evolution of the absorber temperature depend on the load used. In addition, a significant improvement in absorber temperature and water boiling time was observed with the addition of solar reflectors. For example, the absorber temperature was increased by up to 40 °C and the water boiling time was reduced by more than 120 min in the case of triangle-type furnaces.

Analiza porównawcza wybranych metod kalibracji kamery termowizyjnej z chłodzonym detektorem pracującym w zakresie MWIR

For accurate remote temperature measurement with a thermal imaging camera, it is necessary to perform radiometric calibration. This allows the radiative parameters of an object, and therefore its temperature, to be related to the response of the infrared detector observing it. The article presents the basic concepts related to radiometric calibration and various factors influencing its effectiveness. The most common calibration methods were also reviewed, and then two of them were implemented and compared on a specially constructed laboratory station, using proprietary software and equipped with a cooled infrared camera, operating in the MWIR range. The camera was calibrated in the temperature range from 20 °C to 50 ° C. The comparison of methods was carried out on the basis of a series of temperature measurements, analysis of absolute and relative errors, as well as analysis of the dispersion of the measured temperature values.

Metoda pomiaru temperatury ciała człowieka za pomocą kamery termowizyjnej

Measurement and monitoring of human physiological parameters play an important role in many applications such as health care, sports training and prevention of disease spread. Dynamic changes in physiological parameters can reveal not only changes in a patient’s physiological state and function, but also be used to assess a person’s activity status, fitness and fatigue. Body temperature is among the most important human physiological parameters for assessing basic vital functions, apart from heart rate, blood pressure and respiratory rate. In medical practice, various types of measuring instruments are used to measure temperature, such as liquid thermometers, electronic thermometers, non-contact ear thermometers, non-contact forehead thermometers. Liquid and electronic thermometers require the appropriate sensors to be connected to a person, which may be undesirable or impossible as, for example, in newborns or during sports training. Non-contact thermometers operate over short distances and often force a specific position of the person during the measurement. In addition, the above body temperature measurement techniques require direct supervision by medical personnel, which often reduces the effectiveness and efficiency of screening temperature measurement. In screening temperature measurements of a large number of people, especially those on the move, a measuring thermal imaging camera works well. The article presents a method for measuring human body temperature using a thermal imaging camera. The presented method is characterized by high accuracy of temperature measurement, which allows medical use of the obtained measurements. The measurement method has been tested on a test stand and for a selected test sample of people. The measurements and tests carried out confirmed the possibility of obtaining temperature measurement accuracy with an expanded uncertainty of less than 0.05 K with a resolution of less than 0.1 K.

Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems.

In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms.