Review of current thermal imaging temperature calibration and evaluation facilities, practices and procedures, across EURAMET (European Association of National Metrology Institutes)

McEvoy, H.; Simpson, R.; Machin, G.

doi:10.21611/qirt.2012.334

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…Other sources of inaccuracies in thermal measurements using TEC-less cameras are [ 46 ]: size-of-source effect, distance effect, and environmental effects, among others, which are also present in the cooled cameras.…”

Section: Introductionmentioning

confidence: 99%

Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture

Ribeiro-Gomes

Hernández-López

Álvarez

et al. 2017

Sensors

138

119

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The acquisition, processing, and interpretation of thermal images from unmanned aerial vehicles (UAVs) is becoming a useful source of information for agronomic applications because of the higher temporal and spatial resolution of these products compared with those obtained from satellites. However, due to the low load capacity of the UAV they need to mount light, uncooled thermal cameras, where the microbolometer is not stabilized to a constant temperature. This makes the camera precision low for many applications. Additionally, the low contrast of the thermal images makes the photogrammetry process inaccurate, which result in large errors in the generation of orthoimages. In this research, we propose the use of new calibration algorithms, based on neural networks, which consider the sensor temperature and the digital response of the microbolometer as input data. In addition, we evaluate the use of the Wallis filter for improving the quality of the photogrammetry process using structure from motion software. With the proposed calibration algorithm, the measurement accuracy increased from 3.55 °C with the original camera configuration to 1.37 °C. The implementation of the Wallis filter increases the number of tie-point from 58,000 to 110,000 and decreases the total positing error from 7.1 m to 1.3 m.

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Section: Introductionmentioning

confidence: 99%

Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture

Ribeiro-Gomes

Hernández-López

Álvarez

et al. 2017

Sensors

138

119

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“…Each thermal imager was calibrated following NPL standard calibration procedure, i.e. in accordance with the procedure usually employed for calibration of single spot radiation thermometers as performed by all EUROMET national measurement institutes (see [2]). The imagers were calibrated using four NPL standard blackbody sources [3] with emissivities >0.999, the characteristics of which can be found in table 2.…”

Section: Calibrationmentioning

confidence: 99%

“…Imager non-uniformity sub-sections 1 This test could not be carried out on imager C as it was unavailable at the time of testing. 2 This test could not be carried out Imager C or D as the measurement region cannot be moved from the central region of the FOV.…”

Section: Figmentioning

confidence: 99%

Performance tests of thermal imaging systems to assess their suitability for quantitative temperature measurement

Whittam¹,

Simpson²,

McEvoy³

2014

Proceedings of the 2014 International Conference on Quantitative InfraRed Thermography

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The number of thermal imagers being used for absolute temperature measurement in industry has increased dramatically in the past few years. Due to this it is vital that we have a greater understanding of the performance and limitations of thermal imagers for manufacturing, design and calibration purposes, in particular for applications where they are being used for quantitative temperature measurements. A metrological assessment of six thermal imagers was carried out over their full temperature range using the National Physical Laboratory (NPL) high performance standard blackbody reference sources to identify their accuracy and repeatability. The size-of-source effect, temperature drift due to warm up, image non-uniformity, effects of ambient temperature changes and distance effects were also investigated. Results show that temperature errors for five out of the six imagers fell outside of the manufacturers' stated uncertainty at a distance of 1.0 m from the blackbody reference source. Additionally, a number of the imagers showed poor performance with regard to image non-uniformity, drift, size of source and distance effects. This has implications when the imagers are used for in situations where accurate temperature measurements or temperature differences are required.

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“…A second problem arises from the dependence of a given pixel’s signal level on stray light or signal levels corresponding to surrounding pixels. This confound is known in the thermal sensing and imaging field as size-of-source effect (SSE){11,12,13,14} but is not assessed in the IRT febrile screening standard{7}. A recent conference publication{10} showed this can cause inner canthi surface temperatures to vary by an order of magnitude more than the surface calibration indicated.…”

Section: Introductionmentioning

confidence: 99%

Principles and test methods of non-contact body thermometry

Beall¹,

Askegaard

Berkesch

et al. 2022

Preprint

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Significance: Far infrared (IR) has a long history in thermometry and febrile screening. Concerns have been raised recently over the accuracy of non-contact body thermometry. Clinical testing with febrile individuals constitutes the standard performance assessment. This is challenging to replicate, which may have inadvertently allowed approval of IR systems that are unable to detect fevers. The ability to test performance without relying on febrile participants would have ramifications for public health, especially if this discovered undisclosed differences in accuracy in widely used devices. Aim: Identify foundational issues in, demonstrate principles of, and develop test methods for non-contact body thermometry. Approach: We review foundational literature and identify confounds impeding performance of IR thermography (IRT) and non-contact IR thermometry (NCIT) for febrile screening and demonstrate corrections for their effects, which would otherwise be unacceptable. Almost none of the devices we are aware of compensate for these confounds. We reverse-engineer surface-to-body temperature relations for several FDA-cleared NCITs. We note their similarity to recently reported bias-to-normal behavior in other devices and determine range of body temperatures for which the device would produce a "normal" (non-febrile) output. Finally, we generate predictable elevated face temperatures in healthy subjects and demonstrate this in several devices. Results: The surface-to-body relationships for two IRT and one NCIT were linear, while all others exhibited nonlinear bias-to-normal behavior that produce normal temperatures when presented with surface temperatures ranging from hypothermia to moderate-to-severe fever. The test method was used in healthy, non-febrile subjects to generate elevated temperatures corresponding to body temperatures from 97.35F to 102.45F. Three out of five systems had negligible sensitivity. Conclusions: This demonstrates an alternative evaluation method without the limitations and risks of febrile patients. These results indicate many devices may be unusable for body thermometry and may be providing a false sense of security for public health surveillance.

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Review of current thermal imaging temperature calibration and evaluation facilities, practices and procedures, across EURAMET (European Association of National Metrology Institutes)

Cited by 4 publications

References 4 publications

Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture

Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture

Performance tests of thermal imaging systems to assess their suitability for quantitative temperature measurement

Principles and test methods of non-contact body thermometry

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