Infrared Camera Accuracy and Uncertainty in Plain Language

It’s tough to trust measurements from instruments when you don’t have a clear understanding of how their sensitivity and accuracy is derived, and many times infrared cameras fall in this category. Additionally, discussions of infrared camera measurement accuracy typically involve complex terms and jargon that can be confusing and misleading. This can ultimately prompt some researchers to avoid these tools altogether. However, by doing so, they miss out on the potential advantages of thermal measurement for R&D applications. In the following discussion, we strip away the technical terms and explain measurement uncertainty in plain language, providing you with a foundation that will help you understand IR camera calibration and accuracy.

Camera Accuracy Specs and the Uncertainty Equation

You’ll notice that most IR camera data sheets show an accuracy specification such as ±2ºC or 2% of the reading. This specification is the result of a widely used uncertainty analysis technique called “Root‐Sum‐of‐Squares”, or RSS. The idea is to calculate the partial errors for each variable of the temperature measurement equation, square each error term, add them all together, and take the square root. While this equation sounds complex, it’s fairly straightforward. Determining the partial errors, on the other hand, can be tricky.

“Partial errors” can result from one of
several variables in the typical IR camera
temperature measurement equation,

  • Emissivity
  • Reflected ambient temperature
  • Transmittance
  • Atmosphere temperature
  • Camera response
  • Calibrator (blackbody) temperature

Click here to download full article.

Application Story


How do you measure the heat of an object that is moving fast or changing temperature rapidly? Traditional temperature measurement tools such as thermocouples or spot pyrometers don’t offer the resolution or speed needed to fully characterize high speed thermal applications. These tools are impractical for measuring an object in motion – or at the very least, provide an incomplete picture of an object’s thermal properties.

In contrast, an infrared camera can measure temperature across an entire scene, capturing thermal readings for each pixel. Infrared cameras can offer fast, accurate, non-contact temperature measurement. By choosing the correct type of camera for your application, you will be able to gather reliable measurements at high speeds, produce stop-motion thermal images, and generate compelling research data.


Measuring temperature across a broad area, instead of spot by spot, can help researchers and engineers make better-informed decisions about the systems they’re testing. Since thermocouples and thermistors require contact, they only provide data from one location at a time. In addition, small test subjects can only fit a few thermocouples at one time. Attaching them may actually change the temperature reading by acting as a heat sink. Non-contact measurement is possible with a pyrometer – also called an infrared (IR) thermometer—but just like thermocouples, pyrometers only measure a single point.

Infrared cameras produce images from the radiation emitted by objects above absolute zero. By providing a temperature measurement for each pixel, researchers are able to see and measure temperature across a scene without contact. Because IR cameras offer more data than thermocouples or pyrometers and can track changes in temperatures over time, they work well for research and engineering purposes.


There are two types of infrared detectors: thermal and quantum. Thermal detectors such as microbolometers react to incident radiant energy which heats the pixels and creates a change in temperature that is reflected in a change in resistance. These cameras do not require cooling and cost less than quantum detector cameras.

Cooled quantum detectors are made from Indium Antimonide (InSb), Indium Gallium Arsenide (InGaAs), or Strained Layer Superlattice. These detectors are photovoltaic, meaning photons strike the pixels and are converted into electrons that are stored in an integration capacitor. The pixel is electronically shuttered by opening or shorting the integration capacitor.

“Quantum detectors are intrinsically faster than microbolometers – and the main reason for that is the microbolometers have to change temperature,” explains Dr. Robert Madding, President of RPM Energy Associates. A pioneer in the infrared industry, Dr. Madding has more than 35 years of experience in infrared thermography applications and training.

Click here to download full article.

From “Guess” to “Best”

How infrared cameras are increasing accuracy and insight in product testing

Infrared (IR) cameras may be best known for their use in military and security applications. Yet the same attributes that enable IR cameras to thrive in these environments – namely their ability to detect infrared radiation and form an image with it – make them ideal tools for product testing and product development in the medical devices field.

Once thought too expensive for common use in the product testing process, today’s IR cameras are more affordable than ever. They serve as a strategic testing tool that speeds product development by providing major data-gathering advantages over legacy approaches to temperature measurement. These advantages can lead to insights critical to preventing costly product failures and safety hazards, providing operations that use them with an immediate and ongoing return on investment.

As medical device manufacturers develop new products, the key temperature measures they must understand, track, and manage include: understanding the ways in which heat impacts medical device performance, identifying hot spots and temperature spikes, and knowing how, and the rate at which, materials in a device heat up and cool down. Yet even as the rate of innovation in the medical device field has increased, temperature measurement approaches have remained relatively unchanged.

Two Types of Temperature Measurement, One Common Problem

Two types of temperature measurement tools are prevalent today in medical device testing: probes and pyrometers. First, let’s consider probes, which include thermocouples, resistance temperature detectors (RTDs), and thermistors. The problem displaying a fast thermal transient. Measuring this rapid heating accurately in the design phase requires rapid temperature sampling and measurement. If you are using a single probe to make this measurement, you are missing something. You might miss the true maximum temperature to which the device has heated, or a temperature spike during the heating process. What’s worse, you won’t even know what you have missed, which effectively means you are basing product design and performance decisions on bad data. When you don’t sample fast enough, you don’t know what you don’t know.

Click here to download full article.

FLIR Thermal Science Cameras Support Medical Research

Renowned US University uses FLIR cameras to study the effect of temperature on tissue autofluorescence.

Autofluorescence spectroscopy can be used for the purpose of surgical guidance, for example as an imaging technique for delineating surgical margins during cancer excisions (e.g. to be able to identify cancerous tissue close to the margin of normal tissue). As such, by studying autofluorescence, universities are trying to bridge the gap between fundamental science and their practical applications to healthcare.

Effect of temperature on autofluorescence

Despite its use in biomedical research, the relationship between autofluorescence and temperature in tissue has not been explicitly defined.

Many past studies have often assumed a constant temperature during measurements where in vivo experiments were assumed to be at body temperature and in vitro experiments were assumed to be at room temperature. However, there are instances in which the temperature may vary greatly such as during ablation surgeries. In these cases, an understanding of temperature effects on tissue autofluorescence is potentially crucial for accurate interpretation of results during these procedures.

In a series of preliminary experiments aided by the use of a FLIR A655sc thermal imaging camera, researchers from a renowned US university have shown an inverse relationship between temperature and autofluorescence for ex vivo human tissue.

Test set-up

A spectroscopy system equipped with a dual-excitation probe was used to measure the autofluorescence and diffuse reflectance of ex vivo human muscle tissue. Excitation light was provided by a 785 nm diode source while near-infrared autofluorescence emissions were collected by a charge coupled device (CCD) at a spectral resolution of 3.15 nm. The tissue’s temperature was continuously measured by a FLIR A655sc thermal imaging camera.

Ex vivo human muscle samples were acquired and stored at -80°C. During experiments, the samples were placed into a glass beaker and measurements were taken as the samples were allowed to passively warm up to room temperature. Once the sample reached 20°C, the sample was then submerged saline and gradually heated by a hotplate with measurements recorded at every 5°C increase in temperature.

Click here to download full article.

Contact Us

We would love to hear from you. Please take a few moments to fill out the requested information below, or contact us through one of our direct emails.