Interpol questioned documents review 2019-2022

Date determination using a combination of Raman and video spectroscopy for the examination of forged documents containing pre-inked stamp impressions

The examination of stamp impressions is a routine task for questioned document examiners (QDEs) in determining the authenticity of disputed documents. Some studies have provided methods for date determination of stamp impressions, but each single method has its own limitations, so date determination of stamp impressions remains a challenge in case work. This study reports on the real case of a forged contract, in which pre-inked stamp impressions were made on blank paper without the knowledge of the stamp owner. The combination of Raman and video spectroscopy is demonstrated to be a novel method for the date determination of these impressions. In addition to conventional morphological examination methods, video spectroscopy (VS) images were combined with Raman spectroscopy to identify ink components and the distribution of pre-inked impressions. These characteristics vary with the time of stamping, especially after re-inking, and can thus be used to date forged documents. Specifically, spectral analysis of the ink provided a regular representation of temporal variations based on reference stamp samples, which were mutually confirmed by morphological analysis. This approach combines multiple analysis methods to provide diverse evidence for characterizing the tampering and dating the impressions. The results suggest the included stamp impressions were genuine and made on a blank sheet of paper prior to printing the content of the agreement. The five questioned impressions were not entirely consistent in terms of generation time, and none of them were stamped on the nominated date.

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.