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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 skewness and kurtosis based algorithms, the application of the Fourier transform known as Pulsed Phase Transform, or the Principal Component Analysis. They are applied to the quality analysis of different welds of stainless steel plates containing defects such as top and back shielding gases ausence, lack of penetration or perforation in variable thickness plates. The resulting images are compared using the SNR parameter value, which should be higher than 0dB if automated detection of defects is required. The performance of each processing technique to detect different defects is analysed.

Signal to noise ratio (SNR) comparison for pulsed thermographic data processing methods applied to welding defect detection