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Feature Extraction and Pattern Recognition with Fusion Classification in Infrared Thermal Imaging for Serial Number Restoration

NCJ Number
304638
Author(s)
Anit Gurung
Date Published
2020
Length
122 pages
Annotation

This dissertation reports on a project that assessed a procedure for recovering defaced serial numbers with marginal human error, based on a semi-automated, nondestructive method using lock-in thermography (LIT) and pattern recognition technique.

 

Abstract

One chapter outlines a review of relevant literature and background information for serial number restoration, feature extraction using infrared lock-in thermography, and image analysis. This is followed by a chapter that describes the project’s experimental design, including sample preparation, environment, and control variables to collect thermal imaging data based on the LIT review. A chapter provides results for various samples based on ACIP applied to images generated by LIT analysis. The project concludes that the success of the revised non-destructive method on all samples shows the possibility of its use as a standard method for serial number restoration. The experiments validate the flexibility and consistency of the lock-in procedures across varying defacing, techniques, stamping, and samples. ACIP is a robust method for features pattern recognition to identify the defaced serial number and non-stamped areas regardless of the degree of contrast between them. With fusion classification, the risk of misclassification was minimized, assuring the correct identification of a number or letter. Future work is described. Extensive figures, tables, and references

 

Date Published: January 1, 2020