KEYWORDS: Cameras, Calibration, Stereoscopic cameras, 3D modeling, 3D metrology, Infrared cameras, Thermography, 3D vision, 3D image processing, Stereo vision systems
Thermal imaging can be used to characterize heated objects in numerous applications, including security and surveillance, where it is vital to locate an object within a 3D space. This can be achieved with stereoscopic vision, where optical sensors are used to construct a 3D image of the space it is looking at. In order to enhance computer vision research in the thermal modality, stereo thermal-infrared camera calibration must be precise and effective. This research presents a calibration board for thermal stereo vision systems that allows for visual thermal contrast and corner detection within the pattern. In an unstructured and dynamic environment, this thermal stereo vision provides a 3D volumetric measurement for depth estimation of the whole scene within the optical sensors’ combined field of view. Experiments are carried out in the lab, with a mean calibration re-projection error of 0.4 pixel and it is estimated the accuracy of 97.26% at a distance of around 6m for 3D depth measurement.
The process of geometric camera calibration for long-wave infrared (LWIR) camera is essential for determining the camera’s intrinsic and extrinsic parameters, which maps 3D world coordinate points onto 2D image coordinate points. In this paper, new calibration board materials are proposed for making a plane checkerboard to calibrate the LWIR camera. These materials are low-cost items and, to the best of our knowledge, has not been used so far for calibration of infrared camera. The resulting calibration board exhibited high thermal infrared image contrast and showed consistent checkerboard corners’ detection to accomplish the geometric calibration of LWIR wavebands camera. The suggested method is tested using three different LWIR cameras in an indoor environment. The quality of new proposed board thermal imaging is compared with existing calibration board made by paint. The calibration approach is experimented using “MATLAB Single Camera Calibrator Tool” for each of the three LWIR cameras and showed that the overall calibration mean reprojection error is less than 0.35 pixel. The proposed calibration board is beneficial in terms of precision, low-cost built-up and easy reusability.
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