Abstract:
This work introduces a novel approach for forgery detection based on the spectroscopy
of documents’ matters. The proposed approach uses concepts from network science to
generate a weighted network of spectrums for both the original and questioned
documents together. The nodes of the network represent the spectrums and the edges
15 are the correlations among them. The detection method is based on the number of
clusters obtained from the tested network using our modified version of the Louvain
algorithm. The spectrums of inks and papers used in printing the documents were
obtained using Laser-Induced Breakdown Spectroscopy (LIBS) technology. The results
of the proposed approach can be visually interpreted, which is more comfortable and
20 familiar to investigators. The proposed approach was tested under a variety of cases
such as inkjet prints, laser prints, and different kinds of printing papers. The findings
showed that the proposed approach always successful in distinguishing different kinds
of documents with an accuracy of 100%. Finally, the proposed approach is considered
simple and does not need complex computations compared to the approaches in the
25 literature.