TY - JOUR
T1 - A Novel Forensic Tool for the Characterization and Comparison of Printing Ink Evidence
T2 - Development and Evaluation of a Searchable Database Using Data Fusion of Spectrochemical Methods
AU - Trejos, Tatiana
AU - Torrione, Peter
AU - Corzo, Ruthmara
AU - Raeva, Ana
AU - Subedi, Kiran
AU - Williamson, Rhett
AU - Yoo, Jong
AU - Almirall, Jose
N1 - Publisher Copyright:
© 2016 American Academy of Forensic Sciences.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - A searchable printing ink database was designed and validated as a tool to improve the chemical information gathered from the analysis of ink evidence. The database contains 319 samples from printing sources that represent some of the global diversity in toner, inkjet, offset, and intaglio inks. Five analytical methods were used to generate data to populate the searchable database including FTIR, SEM-EDS, LA-ICP-MS, DART-MS, and Py-GC-MS. The search algorithm based on partial least-squares discriminant analysis generates a similarity "score" used for the association between similar samples. The performance of a particular analytical method to associate similar inks was found to be dependent on the ink type with LA-ICP-MS performing best, followed by SEM-EDS and DART-MS methods, while FTIR and Py-GC-MS were less useful in association but were still useful for classification purposes. Data fusion of data collected from two complementary methods (i.e., LA-ICP-MS and DART-MS) improves the classification and association of similar inks.
AB - A searchable printing ink database was designed and validated as a tool to improve the chemical information gathered from the analysis of ink evidence. The database contains 319 samples from printing sources that represent some of the global diversity in toner, inkjet, offset, and intaglio inks. Five analytical methods were used to generate data to populate the searchable database including FTIR, SEM-EDS, LA-ICP-MS, DART-MS, and Py-GC-MS. The search algorithm based on partial least-squares discriminant analysis generates a similarity "score" used for the association between similar samples. The performance of a particular analytical method to associate similar inks was found to be dependent on the ink type with LA-ICP-MS performing best, followed by SEM-EDS and DART-MS methods, while FTIR and Py-GC-MS were less useful in association but were still useful for classification purposes. Data fusion of data collected from two complementary methods (i.e., LA-ICP-MS and DART-MS) improves the classification and association of similar inks.
KW - Data fusion
KW - Database
KW - Document examination
KW - Forensic science
KW - Ink
KW - Spectrochemical
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U2 - 10.1111/1556-4029.13109
DO - 10.1111/1556-4029.13109
M3 - Article
C2 - 27122411
AN - SCOPUS:84963613144
SN - 0022-1198
VL - 61
SP - 715
EP - 724
JO - Journal of Forensic Sciences
JF - Journal of Forensic Sciences
IS - 3
ER -