Ricerc@Sapienza

Infrared Non-destructive Testing (IRNDT) applications are unequivocally expanded and portend a commodity to
improve the quality of defect detection in different fields such as aviation and industrial methods to arts and
archaeology. The proposed approach focuses on the application of low-rank sparse principal component thermography
(Sparse-PCT or SPCT) to assess the advantages and drawbacks of the method for non-destructive
testing. For benchmarking the approach, two types of infrared image sets are tested: the Square Pulse
Thermography (SPT) method for two hybrid composites (carbon and flax fiber reinforced epoxy), and passive
infrared test of Bell Tower and the University of L’Aquila (AQ) faculty’s wall infrared sets. The quantitative
assessment of the approach is also compared for every method and indicate considerable segmentation performance
where other similar approaches were not able to detect the defects. SPCT performance was compared
to some popular decomposition methods such as principal component thermography (PCT), candid covariancefree
incremental principal component thermography (CCIPCT), non-negative matrix factorization (NMF) using
gradient descent (GD) or non-negative least square (NNLS). The comparative results demonstrate the considerable
performance while the other methods failed.