Range, Resolution and FOV Calculator
Determine the optimum camera and lens combination for your application.
 
 
Camera Selection
Camera Model
Pixel pitch (µm)
H (µm)
 
V (µm)
 

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Number of Pixels
H-pixels
 
V-pixels
 
Detector Size (mm)
H-size
 
V-size
 
Field of View
Lens focal length mm
Field of View (FOV) (degrees) °
H-FOV
 
V-FOV
 
D-FOV
 
 
Pixel Field of View (IFOV) (mrad)
H-FOV
 
V-FOV
 
 
Range Parameters
Range to object meters
Field of View at Range (meters)
H-FOV
 
V-FOV
 
 
Pixel Field of View at Range (cm)
H-IFOV
 
V-IFOV
 
 
Detection Range
H-Size of object meters
Max Detection Range (2 pixels)
% of display
Range (meters)
 
% of H display
 
 
Max Recognition Range (8 pixels)
% of display
Range (meters)
 
% of H display
 
Max Identification Range(13 pixels)% of display
Range (meters)
 
% of H display
 
 
Infrared Camera Description and Historical Information
 
This Infrared Camera Range Calculator enables the user to easily estimate the maximum range from which an object can be detected when using various infrared camera platforms. It is important to note that these estimates assume that range performance is based solely on image quality yielding a method of estimation that's simple to implement. The estimates are based solely on the object size, distance, camera objective lens and camera detector parameters. Object temperature, emissivity, atmospheric conditions, reflectivity and other factors are not considered. In this regard, the object size and focal length of the objective lens are variables to be entered by the user. The spreadsheet also provides information as to the angular and spatial field-of-view of different camera systems at a specified range.
 
The calculations used here are based on the "Johnson Criteria" which were developed many years ago by John Johnson, a scientist at the US Army Night Vision Lab (Night Vision & Electronic Sensors Directorate). Johnson was working to develop methods of predicting target detection, recognition, and identification. He was working with volunteer observers using image intensifier equipment and quantified the volunteer observer's ability to identify scale model targets under various conditions. His experiments produced the first empirical data on perceptual thresholds. The so-called Johnson Criteria have been the basis for many models that predict the performance of sensor systems under different environmental and operational conditions. According to the Johnson Criteria, the minimum resolution (pixels on target) required to achieve a 50% probability that an observer can discriminate an object at a certain range to the specified level are:
 
  • Detection - an object is present: 2 +1/-0.5 pixels
  • Recognition - the type object can be discerned, a person vs. a car: 8 +1.6/-0.4 pixels
  • Identification - a specific object can be discerned, a woman vs. a man, the specific car: 12.8 +3.2/-2.8 pixels
    • We hope this information is helpful! Please feel free to email us comments.
 
 
DISCLAIMER: We have made every attempt to provide accurate information. However, we cannot accept any responsibility for errors or inaccuracies. Should you require assistance, please contact us directly. Thank you.