Large building quantitative inspection needs both automatic correction of perspective distortion and precise air and surface temperature measurement. Unfortunately these operations are heavily time consuming if performed manually by a human operator. We present a dedicated algorithm devoted to this task. The procedure first of all detects suitable reference structures put in the field of view, by means of a visual image processing and identifies the 3D position of the wall. The second step matches the thermogram with the visual image of the object. The third step performs an inverse perspective projection applying a thermal camera model, the output is a corrected radiance field. The fourth step measures the air temperature on the reference and the surface temperature map. The surface temperature can be obtained by absolute, relative or differential methods mainly depending on object emissivity value and its spatial distribution.
[1]
Ermanno G. Grinzato,et al.
Automatic thermal reference detection in thermographic images
,
1990,
Defense, Security, and Sensing.
[2]
Roger Y. Tsai,et al.
Techniques for Calibration of the Scale Factor and Image Center for High Accuracy 3-D Machine Vision Metrology
,
1988,
IEEE Trans. Pattern Anal. Mach. Intell..
[3]
Ermanno G. Grinzato,et al.
Open architecture for multispectral computer vision applied to both visual and infrared bands
,
1990,
Optics & Photonics.
[4]
Richard J. Goldstein.
APPLICATION OF AERIAL INFRARED THERMOGRAPHY TO THE MEASUREMENT OF BUILDING HEAT LOSS.
,
1978
.
[5]
S. N. Flanders.
Measured and expected R-values of 19 building envelopes
,
1985
.