The Use of Johnson’s Criteria for Thermal Camera and Systems Performance

When customers are considering which thermal security camera to buy, one of the first questions to the manufacturers of thermal imagers is usually: “At what distance can the thermal camera detect a target?” In other words, what is the camera’s ability to capture very small details at great distances? When thinking about effective surveillance, it is indeed an excellent benchmark to differentiate one sensor from another.

No matter which manufacturer you buy from, the answer to this question will almost always include the “DRI ranges” expression. DRI refers to the distance at which a target is Detected, Recognized, or Identified based on specific universally accepted parameters. When selecting a suitable sensor for your defense, HLS, or security surveillance needs, these DRI ranges have to be, first, perfectly defined but also assessed with regards to globally adopted industrial standards. Enter Johnson’s criteria.

Key Takeaways

• Learn about the origins of Johnson’s Criteria for the detection of a target.
• Understand the differences between Detection, Recognition and Identification when using thermal cameras.
• Know how to ask a camera manufacturer how to determine the actual detection distance in difference scenarios.

The Origin of Johnson’s Criteria

In 1958, at the first-ever Night Vision Image Intensifier Symposium, John Johnson, a night vision scientist at the U.S. Army’s “Night Vision and Electronic Sensors Directorate” (NVESD), presented a paper named the “Analysis of Image Forming Systems.” Johnson’s paper defined a straightforward system with criteria and methodology for predicting an observer’s ability to find and assess targets using image-intensifying equipment (such as thermal cameras) under various conditions. It worked well, and it was the first of its kind.

Johnson’s Criteria Definitions

Johnson’s model provided definitive criteria for calculating the maximum range at which “Detection, Recognition, and Identification (D, R, and I)” could occur, with a 50% probability of success. Newer methodologies exist today for D, R, and I, such as NVESD’s “Night Vision Image Performance Model” (NV-IPM), but Johnson’s Criteria was groundbreaking. Johnson’s criteria was an accepted standard in the defense industry for many years and is still widely used in the security industry today.

Detection

Johnson defined “detection” as the ability to subtend 1 TV line pair (+/- 0.25 line pairs) across the critical dimension of the subject (this translates to 2 pixels when using an LCD monitor). At the range “detection” occurs, regardless of target type, the observer could detect a subject in the field of view 50% of the time. Today, many security camera companies loosely follow Johnson’s Criteria and define their camera’s “detection” performance range as the ability to subtend either 1.5 or 2 pixels on the target, using various target sizes.

Recognition

Johnson defined “Recognition” as the ability to subtend 4 TV line pairs (+/- 0.8 line pairs) across the critical dimension of the subject (this translates to 8 +/- 1 pixel when using an LCD monitor). At the range “recognition” occurs, regardless of target type, the observer determines the subject, a human or a car, for example, 50% of the time. Today, many security camera companies define “recognition” performance range as the ability to subtend 6 pixels on the target, using various target sizes.

Identification

Johnson defined “Identification” as the ability to subtend 6.4 TV line pairs (+/- 1.5 line pairs) across the critical dimension of the subject (this translates to 12 +/- 3 pixels when using an LCD monitor). At the range “identification” occurs, regardless of target type, the observer could detect the subject. Today many security camera companies loosely follow Johnson’s Criteria and define their camera’s “identification” performance range as the ability to subtend 12 pixels on the target, using various target sizes.

Johnson’s Criteria in the Security Industry

DRI ranges, expressed in kilometers (or miles), can usually be found in the specification table of infrared camera brochures or in a description of the camera’s features. While a beneficial starting point for narrowing down the options and homing in on the best systems, customers would be doing themselves a disservice to only look at DRI as the measurement of Johnson’s criteria varies somewhat across the security industry. Documentation often uses simplified or modified criteria versions but generally follows similar rules.

Typically, most companies use twelve (12) pixels on the target for identification, six (6) for recognition, and two (2) for detection. However, the target size can vary greatly. Usually, the defense industry’s “NATO” target size (2.3×2.3 meters) is used for calculating the performance range for detecting vehicles, but we can find various target sizes for a human target. When selecting your thermal camera, it is worth remembering that in any given document, the target size for a human can range from 1.7-1.83 meters tall and from 0.3- 0.75 meters wide, and factor this into your decision-making process.

The Need to look at the Bigger Picture

Because end-users often place a high value on the written specifications of the camera, marketing departments are under pressure to use performance calculations that make their cameras look better than the competitors. However, since these calculations typically do not consider environmental factors, customers should ask their thermal camera providers to explain the other elements and benefits of each camera they offer and how they will perform in various conditions. A modified approach that considers parameters such as these can better help choose the right thermal camera or system for your needs.