Journal of Spectral Imaging,   Volume 8   Article ID a19   (2019)

Peer reviewed Paper

Restoration of defaced serial numbers using lock-in infrared thermography (Part I)

  • Ikwulono Unobe
  • Lisa Lau
  • John Kalivas
  • Rene Rodriguez
  • Andrew Sorensen
College of Science and Engineering, Idaho State University, 921 S. 8th Avenue, Stop 8023, Pocatello, ID, 83209-8023, USA
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 https://orcid.org/0000-0001-7145-5027
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College of Science and Engineering, Idaho State University, 921 S. 8th Avenue, Stop 8023, Pocatello, ID, 83209-8023, USA
[email protected]
 https://orcid.org/0000-0001-8872-3390
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Department of Civil and Environmental Engineering, Utah State University, 4110 Old Main Hill, Logan, Utah, 84322-4110, USA
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 https://orcid.org/0000-0001-9998-2021
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 Corresponding Author
College of Science and Engineering, Idaho State University, 921 S. 8th Avenue, Stop 8023, Pocatello, ID, 83209-8023, USA
[email protected]
 https://orcid.org/0000-0001-7056-976X
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 Corresponding Author
College of Science and Engineering, Idaho State University, 921 S. 8th Avenue, Stop 8023, Pocatello, ID, 83209-8023, USA
[email protected]
 https://orcid.org/0000-0003-4878-0299
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Infrared thermal imaging is an evolving approach useful in non-destructive evaluation of materials for industrial and research purposes. This study investigates the use of this method in combination with multivariate data analysis as an alternative to chemical etching; a destructive method currently used to recover defaced serial numbers stamped in metal. This process involves several unique aspects, each of which works to overcome some pertinent challenges associated with the recovery of defaced serial numbers. Infrared thermal imaging of metal surfaces provides thermal images sensitive to local differences in thermal conductivity of regions of plastic strain existing below a stamped number. These strains are created from stamping pressures distorting the atomic crystalline structure of the metal and extend to depths beneath the stamped number. These thermal differences are quite small and thus not readily visible from the raw thermal images of an irregular surface created by removing the stamped numbers. As such, further enhancement is usually needed to identify the subtle variations. The multivariate data analysis method, principal component analysis, is used to enhance these subtle variations and aid the recovery of the serial numbers. Multiple similarity measures are utilised to match recovered numbers to several numerical libraries, followed by application of various fusion rules to achieve consensus identification.

Keywords: serial number restoration, lock-in infrared thermography, principal component analysis, Zernike moments, similarity measure

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