Blue Ballpoint Pen Inks Differentiation using Multivariate Image Analysis of Digital Images Captured with PhotoMetrix PRO®

Abstract

In Forensic Documentoscopy, it is frequently questioned if a particular document was written with one or more pens. Different methods have been developed to distinguish pen inks from each other, but some of these techniques require the ink extraction, destructing the document, and other techniques uses high cost instruments. PhotoMetrix PRO ® , an app for mobile devices, is a qualitative and colorimetric analysis tool that applies uni-and multivariate analysis. Amongst them, Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares Discriminant Analysis (PLS-DA) can be obtained from digital images' decomposing data. It is a non-destructive and a simple method, of easily use and low cost. Chemometric knowledge is important for results interpretation. This study aims to evaluate the PhotoMetrix PRO ® capacity on blue ballpoint pens differentiation. Three experiments were performed with different ballpoint pens, including colorful pens as an app functionality control. The results showed appropriate differentiation between colorful ballpoint pens, and there was a satisfactory tendency of separation for different brands of blue ballpoint pens, most used in Brazil. This method is interesting to confirm subjective results, eliminating visual differences, intrinsic for each observer, which can be useful in places with an instrument deficiency, like the Video Spectral Comparator ® . New studies to evaluate writing pressure's

Interpol questioned documents review 2019–2022

“…Gorziza et al [ 390 ] evaluated a commercial application for mobile devices, PhotoMetrix PRO®, for the differentiation of blue ballpoint pen inks. This app is a qualitative and colorimetric analysis tool that applies uni- and multivariate analysis, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares Discriminant Analysis (PLS-DA) from digital images data.…”

O Estudo de Tintas de Canetas Esferográficas: uma Revisão para a Abordagem Pericial em Documentoscopia Forense

“…A ideia é maximizar a informação de homogeneidade interna, dentro dos grupos, e maximizar a heterogeneidade entre os grupos. Estudos de Gorziza et al (2020) e Carvalho et al (2018), por exemplo, demonstraram o uso de PCA e de HCA na diferenciação de tintas de canetas. Nestes estudos, mesmo utilizando o mesmo tipo de amostra (tintas de canetas esferográficas azuis e tintas de canetas esferográficas azuis e pretas, respectivamente), foi possível encontrar diferenças entre as diferentes marcas de canetas, e observou--se que canetas de mesma marca formaram grupamentos próximos.…”

“…Outras técnicas demonstraram a diferenciação de canetas utilizando a análise das tintas sem danificar os documentos, analisando a tinta diretamente no papel. Entre essas técnicas, destacam-se ferramentas como a espectroscopia de infravermelho (SHARMA; KU-MAR, 2017), a espectroscopia de Raman (BORBA; HONORATO; JUAN, 2015), a análise com o equipamento VSC®6000 (Video Spectral Comparator) (SILVA et al, 2014), a comparação de imagens digitais de tintas de canetas com auxílio de um smartphone (GORZIZA et al, 2020), a espectroscopia de emissão em plasma induzido por laser (LIBS) (KULA et al, 2014) e alguns equipamentos de espectrometria de massas, como a espectrometria de massas por tempo de voo (To-F-SIMS) (DENMAN et al, 2010) e a espectrometria de massas por paper spray (PS-MS) . Essas técnicas apresentam vantagens na prática forense, pois possibilitam a manutenção da integridade dos documentos.…”

Application of Multivariate Analysis on Digital Images of Cannabis Sativa L Extracts

“…(HELFER et al, 2017) is a colorimetric analysis tool, developed for mobiles devices, which employs PCA, HCA and PLS methods; this app uses the mobile camera to capture digital images, decomposing them into scores and loadings for multivariate analysis. This app has already been used in environmental analysis (LUMBA UE et al, 2019;GRASEL et al, 2016), in food analysis (BOCK et al, 2018;HELFER et al, 2018) and in Forensic Documentoscopy (GORZIZA et al, 2020;VITTORAZZI et al, 2020).…”