Search Results (21)

Uncooled and shutterless microbolometer cameras are good candidates for infrared imaging systems installed on small satellites or small unmanned aerial vehicles: they are light and passive since no cooling system or mechanical shutter is required and they can be operated at ambient temperatures. However, the radiometric compensation has to be carefully performed to make the system compatible with applications where the radiometric accuracy of the images is mandatory. In this paper, we study the impact of the camera environment to the radiometric accuracy of the images. We propose and test hardware and software solutions to improve this accuracy and the quality of the radiometric images. We show that the radiometric calibration of the camera with our model is valid over a long time period— about 3 years—using in-door experiments. Full article

The detection of impact and depth defects in Glass Fiber Reinforced Polymer (GFRP) composites has been extensively studied to develop effective, reliable, and cost-efficient assessment methods through various Non-Destructive Testing (NDT) techniques. Challenges in detecting these defects arise from varying responses based on the geometrical shape, thickness, and defect types. Long Pulse Thermography (LPT), utilizing an uncooled microbolometer and a low-resolution infrared (IR) camera, presents a promising solution for detecting both depth and impact defects in GFRP materials with a single setup and minimal tools at an economical cost. Despite its potential, the application of LPT has been limited due to susceptibility to noise from environmental radiation and reflections, leading to blurry images. This study focuses on optimizing LPT parameters to achieve accurate defect detection. Specifically, we investigated 11 flat-bottom hole (FBH) depth defects and impact defects ranging from 8 J to 15 J in GFRP materials. The key parameters examined include the environmental temperature, background reflection, background color reflection, and surface emissivity. Additionally, we employed image processing techniques to classify composite defects and automatically highlight defective areas. The Tanimoto Criterion (TC) was used to evaluate the accuracy of LPT both for raw images and post-processed images. The results demonstrate that through parameter optimization, the depth defects in GFRP materials were successfully detected. The TC success rate reached 0.91 for detecting FBH depth defects in raw images, which improved significantly after post-processing using Canny edge detection and Hough circle detection algorithms. This study underscores the potential of optimized LPT as a cost-effective and reliable method for detecting defects in GFRP composites. Full article

Infrared thermography is considered a useful technique for diagnosing several skin pathologies but it has not been widely adopted mainly due to its high cost. Here, we investigate the feasibility of using low-cost infrared cameras with microbolometer technology for detecting skin cancer. For this purpose, we collected infrared data from volunteer subjects using a high-cost/high-quality infrared camera. We propose a degradation model to assess the use of lower-cost imagers in such a task. The degradation model was validated by mimicking video acquisition with the low-cost cameras, using data originally captured with a medium-cost camera. The outcome of the proposed model was then compared with the infrared video obtained with actual cameras, achieving an average Pearson correlation coefficient of more than 0.9271. Therefore, the model successfully transfers the behavior of cameras with poorer characteristics to videos acquired with higher-quality cameras. Using the proposed model, we simulated the acquisition of patient data with three different lower-cost cameras, namely, Xenics Gobi-640, Opgal Therm-App, and Seek Thermal CompactPRO. The degraded data were used to evaluate the performance of a skin cancer detection algorithm. The Xenics and Opgal cameras achieved accuracies of 84.33% and 84.20%, respectively, and sensitivities of 83.03% and 83.23%, respectively. These values closely matched those from the non-degraded data, indicating that employing these lower-cost cameras is appropriate for skin cancer detection. The Seek camera achieved an accuracy of 82.13% and a sensitivity of 79.77%. Based on these results, we conclude that this camera is appropriate for less critical applications. Full article

For uncooled infrared cameras based on microbolometers, silicon caps are often utilized to maintain a vacuum inside the packaged bolometer array. To reduce Fresnel reflection losses, anti-reflection coatings are typically applied on both sides of the silicon caps.This work investigates whether black silicon may be used as an alternative to conventional anti-reflective coatings. Reactive ion etching was used to etch the black silicon layer and deep cavities in silicon. The effects of the processed surfaces on optical transmission and image quality were investigated in detail by Fourier transform infrared spectroscopy and with modulated transfer function measurements. The results show that the etched surfaces enable similar transmission to the state-of-the-artanti-reflection coatings in the 8–12 µm range and possibly obtain wider bandwidth transmission up to 24 µm. No degradation in image quality was found when using the processed wafers as windows. These results show that black silicon can be used as an effective anti-reflection layer on silicon caps used in the vacuum packaging of microbolometer arrays. Full article

As part of the Earth Climate Observatory space mission concept for the direct observation from space of the Earth Energy Imbalance, we propose an advanced camera suite for the high-resolution observation of the Total Outgoing Radiation of the Earth. For the observation of the Reflected Solar Radiation, we propose the use of two multispectral cameras covering the range from 400 to 950 nm, with a nadir resolution of 1.7 km, combined with a high-resolution RGB camera, with a nadir resolution of 0.57 km. For the observation of the Outgoing Longwave Radiation, we propose the use of six microbolometer cameras, with each a spectral bandwidth of 1 μm in the range from 8 to 14 μm, with a nadir resolution of 2.2 km. Full article

Many common thermographic cameras have quite good sensitivity (0.05 °C or better) but limited accuracy, often about ±2 °C. This is not sufficient for quantitative measurements such as human body temperature diagnostics, where an accuracy of 0.3 °C is assumed. A thermographic device with a built-in active reference element for enhanced precision measurement was developed for these purposes. It was adapted for human body temperature diagnostics using face temperature measurements. It is based on a micro-bolometers detector and the reference element is heated to a temperature of 37 °C, which is mostly assumed as decisive for an increased temperature indication. As the reference element is embedded into the device housing, the use of the device can be very flexible. The performed human temperature measurement experiments showed that the accuracy of the introduced device is comparable with the thermographic measurements obtained using an external black body, which is often used for these applications. Full article

Nondestructive testing (NDT) of composite materials is of paramount importance to the aerospace industry. Several NDT methods have been adopted for the inspection of components during production and all through the aircraft service life, with infrared thermography (IRT) techniques, such as line scan thermography (LST) and pulsed thermography (PT), gaining popularity thanks to their rapidity and versatility. On one hand, LST is an attractive solution for the fast inspection of large and complex geometry composite parts during production. On the other hand, PT can be employed for the characterization of composite materials, e.g., the determination of thermal diffusivity and defect depth estimation. In this study, the use of LST with an uncooled microbolometer camera is explored for the identification of artificially produced porosity and barely visible impact damage (BVID) on academic samples. The performance of LST is quantitatively assessed with respect to PT (considered the gold standard in this case) using a high-definition cooled camera through the contrast-to-noise ratio (CNR) criterium. It is concluded that, although in most cases the measured CNR values were higher for PT than for LST (as expected since a high-definition camera and longer acquisition times were used), the majority of the defects were clearly detected (CNR ≥ 2.5) by LST without the need of advanced signal processing, proving the suitability of LST for the inspection of aerospace composite components. Furthermore, the deepest defect investigated herein (z ≈ 3 mm) was detected solely by LST combined with signal processing and spatial filtering (CNR = 3.6) and not by PT (since pulse heating was not long enough for this depth). In addition, PT was used for the determination of the thermal diffusivity of all samples and the subsequent depth estimation of porosity and damaged areas by pulsed phase thermography (PPT). Full article

Thermal vision-based devices are nowadays used in a number of industries, ranging from the automotive industry, surveillance, navigation, fire detection, and rescue missions to precision agriculture. This work describes the development of a low-cost imaging device based on thermographic technology. The proposed device uses a miniature microbolometer module, a 32-bit ARM microcontroller, and a high-accuracy ambient temperature sensor. The developed device is capable of enhancing RAW high dynamic thermal readings obtained from the sensor using a computationally efficient image enhancement algorithm and presenting its visual result on the integrated OLED display. The choice of microcontroller, rather than the alternative System on Chip (SoC), offers almost instantaneous power uptime and extremely low power consumption while providing real-time imaging of an environment. The implemented image enhancement algorithm employs the modified histogram equalization, where the ambient temperature sensor helps the algorithm enhance both background objects near ambient temperature and foreground objects (humans, animals, and other heat sources) that actively emit heat. The proposed imaging device was evaluated on a number of environmental scenarios using standard no-reference image quality measures and comparisons against the existing state-of-the-art enhancement algorithms. Qualitative results obtained from the survey of 11 subjects are also provided. The quantitative evaluations show that, on average, images acquired by the developed camera provide better perception quality in 75% of tested cases. According to qualitative evaluations, images acquired by the developed camera provide better perception quality in 69% of tested cases. The obtained results verify the usability of the developed low-cost device for a range of applications where thermal imaging is needed. Full article

Infrared imaging sensors are frequently used in thermal signature detection applications in industrial, automotive, military and many other areas. However, advanced infrared detectors are generally associated with high costs and complexity. Infrared detectors usually necessitate a thermoelectric heater–cooler for temperature stabilization and various computationally complex preprocessing algorithms for fixed pattern noise (FPN) correction. In this paper, we leverage the benefits of uncooled focal plane arrays and describe a complete digital circuit design for Field Programmable Gate Array (FPGA)-based infrared image acquisition and pre-processing. The proposed design comprises temperature compensation, non-uniformity correction, defective pixel correction cores, spatial image transformation and registration with RGB images. When implemented on Xilinx Ultrascale+ FPGA, the system achieves a throughput of 30 frames per second using the Fraunhofer IMS Digital 17 μm QVGA-IRFPA with a microbolometer array size of 320 × 240 pixels and an RGB camera with a 1024 × 720 resolution. The maximum ratio of the standard deviation to the mean of 0.35% was achieved after FPN correction. Full article

The article presents a new concept—steganography in thermography. Steganography is a technique of hiding information in a non-obvious way and belongs to sciences related to information security. The proposed method, called ThermoSteg, uses a modification of one of the parameters of the thermal imaging camera—integration time—to embed the signal containing hidden information. Integration time changing makes the microbolometer array heat up while reading the sensors. The covert information can be extracted from the stream of thermograms recorded by another thermal camera that observes the first one. The covert channel created with the ThermoSteg method allows the transmission of covert data using a thermal sensor as a wireless data transmitter. This article describes a physical phenomenon that is exploited by the ThermoSteg method and two proposed methods of covert data extraction, and presents the results of experiments. Full article

The miniaturization of thermal infrared sensors suitable for integration with unmanned aerial vehicles (UAVs) has provided new opportunities to observe surface temperature at ultra-high spatial and temporal resolutions. In parallel, there has been a rapid development of software capable of streamlining the generation of orthomosaics. However, these approaches were developed to process optical and multi-spectral image data and were not designed to account for the often rapidly changing surface characteristics inherent in the collection and processing of thermal data. Although radiometric calibration and shutter correction of uncooled sensors have improved, the processing of thermal image data remains difficult due to (1) vignetting effects on the uncooled microbolometer focal plane array; (2) inconsistencies between images relative to in-flight effects (wind-speed and direction); (3) unsuitable methods for thermal infrared orthomosaic generation. Here, we use thermal infrared UAV data collected with a FLIR-based TeAx camera over an agricultural field at different times of the day to assess inconsistencies in orthophotos and their impact on UAV-based thermal infrared orthomosaics. Depending on the wind direction and speed, we found a significant difference in UAV-based surface temperature (up to 2 °C) within overlapping areas of neighboring flight lines, with orthophotos collected with tail wind being systematically cooler than those with head wind. To address these issues, we introduce a new swath-based mosaicking approach, which was compared to three standard blending modes for orthomosaic generation. The swath-based mosaicking approach improves the ability to identify rapid changes of surface temperature during data acquisition, corrects for the influence of flight direction relative to the wind orientation, and provides uncertainty (pixel-based standard deviation) maps to accompany the orthomosaic of surface temperature. It also produced more accurate temperature retrievals than the other three standard orthomosaicking methods, with a root mean square error of 1.2 °C when assessed against in situ measurements. As importantly, our findings demonstrate that thermal infrared data require appropriate processing to reduce inconsistencies between observations, and thus, improve the accuracy and utility of orthomosaics. Full article

We present a real-time THz imaging method using a commercial fiber-coupled photo conductive antenna as the THz source and an uncooled microbolometer camera for detection. This new combination of state-of-the-art components is very adaptable due to its compact and uncooled radiation source, whose fiber coupling allows for a flexible placement. Using a camera with high sensitivity renders real-time imaging possible. As a proof-of-concept, the beam shape of a THz Time Domain Spectrometer was measured. We demonstrate real time imaging at nine frames per second and show its potential for practical applications in transmission geometry covering both material science and security tasks. The results suggest that hidden items, complex structures and the moisture content of (biological) materials can be resolved. We discuss the limits of the current setup, possible improvements and potential (industrial) applications, and we outline the feasibility of imaging in reflection geometry or extending it to multi-spectral imaging using band pass filters. Full article

The formation and evolution of clouds are associated with their thermodynamical and microphysical progress. Previous studies have been conducted to collect images using ground-based cloud observation equipment to provide important cloud characteristics information. However, most of this equipment cannot perform continuous observations during the day and night, and their field of view (FOV) is also limited. To address these issues, this work proposes a day and night clouds detection approach integrated into a self-made thermal-infrared (TIR) all-sky-view camera. The TIR camera consists of a high-resolution thermal microbolometer array and a fish-eye lens with a FOV larger than 160°. In addition, a detection scheme was designed to directly subtract the contamination of the atmospheric TIR emission from the entire infrared image of such a large FOV, which was used for cloud recognition. The performance of this scheme was validated by comparing the cloud fractions retrieved from the infrared channel with those from the visible channel and manual observation. The results indicated that the current instrument could obtain accurate cloud fraction from the observed infrared image, and the TIR all-sky-view camera developed in this work exhibits good feasibility for long-term and continuous cloud observation. Full article

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R² of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R² of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements. Full article

Magnetic hyperthermia treatments utilize the heat generated by magnetic nanoparticles stimulated by an alternating magnetic field. Therefore, analytical methods are required to precisely characterize the dissipated thermal energy and to evaluate potential amplifying or diminishing factors in order to ensure optimal treatment conditions. Here, we present a lock-in thermal imaging setup specifically designed to thermally measure magnetic nanoparticles and we investigate theoretically how the various experimental parameters may influence the measurement. We compare two detection methods and highlight how an affordable microbolometer can achieve identical sensitivity with respect to a thermal camera-based system by adapting the measurement time. Furthermore, a numerical model is used to demonstrate the optimal stimulation frequency, the degree of nanomaterial heating power, preferential sample holder dimensions and the extent of heat losses to the environment. Using this model, we also revisit some technical assumptions and experimental results that previous studies have stated and suggest an optimal experimental configuration. Full article