Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery of the lost data many destructive or non-destructive techniques have been endeavoured so far, which however present several restrictions. In this paper, active infrared thermography has been exploited for the first time in order to assess its effectiveness in restoring paint covered and abraded labels made by means of different manufacturing processes (laser, dot peen, impact, press and scribe). Optical excitation of the target surface has been achieved using pulse, lock-in and step heating. Raw infrared images were analysed with a dedicated image processing software originally developed in Matlab (TM), exploiting several methods, which include thermographic signal reconstruction, guided filtering and logarithmic transformation.

Restoration of abraded and covered marks engraved in steel using active infrared thermography

Sebastiano Piccolo;
2016-01-01

Abstract

Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery of the lost data many destructive or non-destructive techniques have been endeavoured so far, which however present several restrictions. In this paper, active infrared thermography has been exploited for the first time in order to assess its effectiveness in restoring paint covered and abraded labels made by means of different manufacturing processes (laser, dot peen, impact, press and scribe). Optical excitation of the target surface has been achieved using pulse, lock-in and step heating. Raw infrared images were analysed with a dedicated image processing software originally developed in Matlab (TM), exploiting several methods, which include thermographic signal reconstruction, guided filtering and logarithmic transformation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/358723
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