Increased temperature in humans is the symptom of many infectious diseases and it is thus an important diagnostic tool. Infrared temperature measurement methods have been developed and applied over long periods due to their advantage of non-contact and fast measurements. This study deals with a statistical evaluation of the possibilities and limitations of infrared/thermographic human temperature measurement. A short review of the use of infrared temperature measurement in medical applications is provided. Experiments and statistics-based evaluation to confirm the expected accuracy and limits of thermography-based human temperature measurement are introduced. The results presented in this study show that the standard deviation of the thermographic measurement of the eyes maximum temperature was 0.4–0.9 °C and the mean values differences from the armpit measurement were up to 0.5 °C, based on the used IR camera, even though near ideal measurement conditions and permanent blackbody correction were used. It was also shown that a certain number of outliers must be assumed in such measurements. Extended analyses including simulations of true negative/false positive, sensitivity/specificity and receiver operating characteristics (ROC) curves are presented. The statistical evaluation as well as the extended analyses show that maximum eyes temperature is more relevant than a forehead temperature examination.

Pulsed thermography is a common technique for nondestructive testing (NDT) of materials. This study presents the apparent effusivity method for the quantitative evaluation of coating thickness in a one-sided thermal NDT procedure. The proposed algorithm is based on determining a threshold value of apparent effusivity, which can be found for particular coating-on-substrate structures. It has been found that the square root of the time at which the apparent effusivity curve reaches this threshold is proportional to the coating thickness. The efficiency of the proposed approach is demonstrated by analytical modeling and experimentation performed on thermally-sprayed coatings.

Emissivity is a crucial parameter for a quantitative thermography measurement. It influences measured temperature using an infrared camera. Typically, the emissivity is handled by infrared camera software but often for more complex tasks—e.g., setting and controlling the emissivity of individual pixels—a custom-made solution must be created. This can be especially beneficial for active thermography measurement and dynamic building inspection by infrared thermography as many surfaces of interest with different emissivity occur in thermographic data. In literature, one technique for suppressing emissivity occurs most often—the technique used by infrared camera manufacturers. Nonetheless, two other techniques are marginally mentioned. The most complex technique is the one used by infrared camera manufacturers, which allows many parameters to be set, but it is difficult to incorporate it into own solution. In contrast, the second one can be adapted easily, and it uses the relationship between emissivity and the fourth power of temperatures. The third one is a scarcely used technique that occurs for some active thermography measurements, in which a thermographic sequence in counts is divided by a frame when temperature equilibrium is reached. The main goal of this article is to compare these individual techniques from the point of view of the accuracy and possibility of use. The experiment showed that all three methods can be successfully used for the suppression of emissivity influence.

Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major boom between 2020 and 2022 due to the COVID-19 epidemic, but with questionable results. This article does not deal with the precise determination of the temperature of an individual person but focuses on the possibility of using infrared cameras for monitoring the health of the population. The aim is to use large amounts of infrared data from many locations to provide information to epidemiologists so they can have better information about potential outbreaks. This paper focuses on the long-term monitoring of the temperature of passing persons inside public buildings and the search for the most appropriate tools for this purpose and is intended as the first step towards creating a useful tool for epidemiologists. As a classical approach, the identification of persons based on their characteristic temperature values over time throughout the day is used. These results are compared with the results of a method using artificial intelligence (AI) to evaluate temperature from simultaneously acquired infrared images. The advantages and disadvantages of both methods are discussed.

Thermographic testing is an inspection method, which primary indicates a presence of discontinuities in a tested sample. Its application to coatings can indicate a presence of local thickness variations; however, it mostly does not bring a quantitative information about a thickness of the coatings. This contribution is focused on a quantification of the thermographic inspection, which would make possible an evaluation of coating thickness differences. A flash pulse thermographic testing was applied to thermally sprayed coatings. An importance of a precise synchronization of a flash-source and thermographic recording was determined. Different evaluation methods were analyzed and their comparison showed that a time-power transformation method is the most suitable for a quantification of the inspection results.

The contribution describes a fast contactless measurement of a paint thickness non-uniformity using flash pulse thermography. Specimens sprayed by a paint were thermally excited by a flash lamp and temperature responses were recorded by an infrared camera. The recorded sequences were post-processed with Fast Fourier Transform to obtain phase angles. Differences in the resulting images showed phase differences which corresponded to a paint thickness non-uniformity. Furthermore, the phases were correlated with the thickness by means of calibration curve so that the paint thickness could be determined with flash pulse phase thermography measurement. The method showed a promising potential in the contactless evaluation of the paint thickness. Average error of the thickness determination was less than 10 % for samples with paint thickness from 41 to 74 µm on AISI 304 substrate. Advantages, disadvantages and limitations of described method were discussed.