In this paper, the use of a signal to noise ratio (SNR) is proposed for the quantification of the goodness of some selected processing techniques of thermographic images, such as differentiated absolute contrast, skewness and kurtosis based algorithms, pulsed phase transform, principal component analysis and thermographic signal reconstruction. A new hybrid technique is also applied (PhAC-Phase absolute contrast), it combines three different processing techniques: phase absolute contrast, pulsed phase thermography and thermographic signal reconstruction. The quality of the results is established on the basis of the values of the parameter SNR, assessed for the present defects in the analyzed specimen, which enabled to quantify and compare their identification and the quality of the results of the employed technique.

The carbon black has been used in military fabrics to comply with the color requirements and infrared radiation lessening criteria. Currently, military industries don’t distinguish between fabrics with carbon black fibers or with carbon black into dyes or prints. The latter initially allows us to comply with the color specifications in the visible and infrared, but fabrics are degraded with use losing that initial capacity. The inclusion of carbon black in the fiber gets that the fabric doesn’t degrade with the wear, washed and dried, ensuring the accomplishment of the specifications all the time. The use of infrared imaging will allow us to define a method to discriminate those textiles with carbon black in their fibers from those which are dyed or printed.

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