The standard setting of a camera used in Infrared thermography (IRT) is based on the choice of the same values of emissivity and distance for all pixels of a thermal image even if the emissivity depends on the relative position of camera and observed surface. Often this is not a problem. However, the resulting temperature pattern could be inadequate if a body having a complex shape is observed from strongly constrained positions. In order to face this issue, a procedure aimed at providing a correct temperature pattern by using 3D information related to a point cloud is proposed together with its MATLAB implementation (COMAP3 toolbox). For each pixel of a thermal image, the relative position of camera and observed surface is estimated, leading to pixel-specific values of emissivity and distance. The temperature obtained in this way is also mapped onto the point cloud. The effectiveness of the procedure in recognizing areas characterized by peculiar thermal behavior is shown in the case of a historic cylindrical masonry bell tower (Caorle's bell tower, Venice, Italy).
Teza G., Pesci A. (2019). Evaluation of the temperature pattern of a complex body from thermal imaging and 3D information: A method and its MATLAB implementation. INFRARED PHYSICS & TECHNOLOGY, 96, 228-237 [10.1016/j.infrared.2018.11.029].
Evaluation of the temperature pattern of a complex body from thermal imaging and 3D information: A method and its MATLAB implementation
Teza G.
;
2019
Abstract
The standard setting of a camera used in Infrared thermography (IRT) is based on the choice of the same values of emissivity and distance for all pixels of a thermal image even if the emissivity depends on the relative position of camera and observed surface. Often this is not a problem. However, the resulting temperature pattern could be inadequate if a body having a complex shape is observed from strongly constrained positions. In order to face this issue, a procedure aimed at providing a correct temperature pattern by using 3D information related to a point cloud is proposed together with its MATLAB implementation (COMAP3 toolbox). For each pixel of a thermal image, the relative position of camera and observed surface is estimated, leading to pixel-specific values of emissivity and distance. The temperature obtained in this way is also mapped onto the point cloud. The effectiveness of the procedure in recognizing areas characterized by peculiar thermal behavior is shown in the case of a historic cylindrical masonry bell tower (Caorle's bell tower, Venice, Italy).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.