化学
傅里叶变换红外光谱
班级(哲学)
光谱学
分析化学(期刊)
模式识别(心理学)
生物系统
人工智能
有机化学
化学工程
物理
量子力学
计算机科学
工程类
生物
作者
Erklaylle G.C. Silva,Carolina S. Silva,Maria Fernanda Pimentel
标识
DOI:10.1016/j.saa.2024.124961
摘要
One of the great challenges of document analysis is determining document forgeries. The present work proposes a non-destructive approach to discriminate natural and artificially aged papers using infrared spectroscopy and soft independent modeling by class analogy (SIMCA) algorithms. This is of particular interest in cases of document falsifications made by artificial aging, for this study, SIMCA, and Data-Driven SIMCA (DD-SIMCA) classification models were built using naturally aged paper samples, taken from three time periods: 1st period from 1998 to 2003; 2nd period from 2004 to 2009; and 3rd period from 2010 to 2015. Artificially aged samples (exposed to high temperature or UV radiation) were used as test sets. Promising results in detecting document falsifications related to aging were obtained. Samples artificially aged at high temperature were correctly discriminated from the authentic samples (naturally aged) with 100% accuracy. In contrast, the samples under the photodegradation process showed a lower classification performance, with results above 90%.
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