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Fourier Transform Hyperspectral Visible Imaging and the Nondestructive Analysis of Potentially Fraudulent Documents
- Source :
- Applied Spectroscopy. 60:833-840
- Publication Year :
- 2006
- Publisher :
- SAGE Publications, 2006.
-
Abstract
- The work presented in this paper details the design and performance characteristics of a new hyperspectral visible imaging technique. Rather than using optical filters or a dispersing element, this design implements Fourier transform spectroscopy to achieve spectral discrimination. One potentially powerful application of this new technology is the nondestructive analysis and authentication of written and printed documents. Document samples were prepared using red, blue, and black inks. The samples were later altered using a different ink of the same color. While the alterations are undetectable to the naked eye, the alterations involving the blue and black inks were easily detected when the spectrally resolved images were viewed. Analysis of the sample using the red inks was unsuccessful. A 2004 series $20 bill was imaged to demonstrate the application to document authentication. The results argue that counterfeit detection and quality control during printing are plausible applications of Fourier transform hyperspectral visible imaging. All of the images were subjected to fuzzy c-means cluster analysis in an effort to objectively analyze and automate image analysis. Our results show that cluster analysis can distinguish image features that have remarkably similar visible transmission spectra.
- Subjects :
- Paper
Chemical imaging
medicine.medical_specialty
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Analytical chemistry
Documentation
01 natural sciences
Fourier transform spectroscopy
010309 optics
symbols.namesake
0103 physical sciences
medicine
Optical filter
Instrumentation
Spectroscopy
Authentication
Fourier Analysis
business.industry
Spectrum Analysis
Fraud
010401 analytical chemistry
Hyperspectral imaging
Pattern recognition
Models, Theoretical
Sample (graphics)
0104 chemical sciences
Spectral imaging
Fourier transform
symbols
Artificial intelligence
business
Subjects
Details
- ISSN :
- 19433530 and 00037028
- Volume :
- 60
- Database :
- OpenAIRE
- Journal :
- Applied Spectroscopy
- Accession number :
- edsair.doi.dedup.....f715b241cd1a7f23703636813f86f7de
- Full Text :
- https://doi.org/10.1366/000370206778062093