Spatial Calibration for Accurate Long Distance Measurement Using Infrared Cameras
A new spatial calibration procedure has been introduced for infrared optical systems developed for cases where camera systems are required to be focused at distances beyond 100 meters.
All commercially available camera systems have lenses (and internal geometries) that cannot perfectly refract light waves and refocus them onto a two-dimensional (2D) image sensor. This means that all digital images contain elements of distortion and thus are not a true representation of the real world. Expensive high-fidelity lenses may have little measurable distortion, but if sufficient distortion is present, it will adversely affect photogrammetric measurements made from the images produced by these systems. This is true regardless of the type of camera system, whether it be a daylight camera, infrared (IR) camera, or camera sensitive to another part of the electromagnetic spectrum.
The most common examples of large-scale lens distortions are known as barrel and pincushion effects, which are illustrated in figure 1. If these images were a truly planar reproduction of the real world, the curved lines in the images would appear as straight lines. Essentially, this can be thought of as the focal length (conversion from pixel distance to real-world distance) not being uniform throughout the image. Spatial calibration aims to build a transform to correct for large-scale distortion effects and effectively flatten an image so that the focal lengths (x and y) are uniform throughout the field of view.
Some photographic applications require that the focus of a camera lens be set to a long distance (beyond 200 meters). This allows distant objects to appear sharply in focus as opposed to indoor laboratory environments where the focus may be set to a much closer distance. Some optical systems used for visual navigation or object tracking fall into the long-distance focus category. This may also apply to situations where far-away objects or features are tracked for the purposes of image stabilization. Since a change in focus affects the intrinsic parameters of the camera and possibly the distortion model, it is necessary to perform a calibration at the focus at which measurements will be made. When the focus is set to a far distance (over 200 meters), conventional methods for laboratory calibration are not feasible because the calibration targets required would be too large and placed too far away to fit indoors.
The most widely used spatial calibration tool was developed by Yvez-Bouquet and is now included with its own graphical user interface (GUI) in the MATLAB Image Processing Toolbox (ref. 2). This convenient and automated method makes use of a flat target board of any size with a checker pattern. The tool works by estimating the intrinsic and extrinsic properties of a camera to allow the conversion from 2D image coordinates to the 2D real-world coordinates of the checkerboard intersections. To do this, a sequence of images of the target board is recorded from various angles and in various positions throughout the field of view. The operator can either use a stationary camera and move the target board or move the camera around a stationary target board. Sufficiently capturing the target at various angles is critical for estimating the extrinsic parameters of the camera system, while sufficiently recording images of the target throughout the field of view is critical for accurately building a model of the camera distortion field.
An investigation into various construction techniques for medium-scale IR calibration boards (larger than would be used in laboratory environments, but smaller than an ideal outdoor array) was conducted to find a design that exhibited the greatest contrast between the dots and the background. A variety of target boards were made of 4 × 8 ft (1.2 × 2.4 m) sheets of foil-faced polyisocyanurate insulation board. At this size and of this material, the boards could still be moved and twisted around by a single person. During construction, a precision-printed template was used to position different types of dots on the surface. Experiments included varying paint colors, sheens, and materials.
The goal of the experiment was to identify which construction technique provided the most consistent contrast for mid-wave IR cameras. High contrast would be needed both when the camera is tilted up (reflecting the sky) and down (reflecting the ground). Based on the images collected, it was determined that using a calibration board with a high-gloss white paint and matte black paint for the dots provided the most consistent contrast. The best performance was achieved when briefly exposing the surface of the calibration board to the sun for a period of approximately 20 seconds. This warmed the matte black dots quicker than the white background, increasing contrast in the IR spectrum and making the dots easy to detect using an automated circle-finding algorithm.
This work was performed by Ryan Decker for the Army Combat Capabilities Development Command Armaments Center. For more information, download the Technical Support Package (free white paper) below. ARMET-21034
This Brief includes a Technical Support Package (TSP).
Spatial Calibration for Accurate Long Distance Measurement Using Infrared Cameras
(reference ARMET-21034) is currently available for download from the TSP library.
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