通过判别分析,基于三维轮廓对激光打印机和墨盒进行预测。

IF 2.2 3区 医学 Q1 MEDICINE, LEGAL Forensic science international Pub Date : 2024-08-06 DOI:10.1016/j.forsciint.2024.112186
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引用次数: 0

摘要

在检查有问题的文件时,打印机来源预测是一项重要任务。虽然一些研究提供了预测文件源打印机的方法,但随着兼容耗材的出现,打印机预测可能会变得更加复杂和困难。预测更换墨盒后的源打印机和识别打印机墨盒的来源是目前研究中很少涉及的未决问题。在此,我们介绍一种新技术,用于预测激光打印机的制造商、型号和用于生成给定文档的墨盒(即兼容墨盒和原装墨盒)。我们收集了使用 8 台激光打印机和 247 个墨盒制作的文档样本,建立了一个数据集。常见的制造商包括惠普、佳能、联想和爱普生。在获得打印字符的白光图像和三维轮廓图像后,受询文件检验员(QDEs)使用显微镜进行了形态分析。此外,还使用算法提取和分析了一系列图像的显微图像特征。然后,使用六种高维还原算法来获得打印机之间和打印机内部的差异,以及墨盒之间和墨盒内部的差异。最后,我们进行了主成分分析(PCA)和判别分析。对于 40% 的样本,我们采用了混合判别分析(MDA)和固定判别分析(FDA)来预测用于生成被质疑打印文档的激光打印机的制造商、型号和墨盒;其余 60% 的样本构成了训练数据集。在制造商、型号和墨盒的预测方面,我们的方法取得的平均准确率分别为 95.5%、97.5% 和 90.2%。因此,即使打印机装入了不同的墨盒,这项技术也能合理地帮助预测激光打印机的制造商、型号和墨盒。
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Prediction of laser printers and cartridges based on three-dimensional profiles via discrimination analysis

Printer source prediction is an important task when examining questioned documents. While some research has provided methods to predict the source printer of documents, with the advent of compatible consumables, printer prediction could become more complex and difficult. Predicting the source printer after replacing cartridges and identifying the source of printer cartridges are unresolved issues that are rarely addressed in current research. Herein, we introduce a novel technique to predict the manufacturer, model, and cartridges of laser printers (i.e., compatible, and original cartridges) used to produce a given document. Document samples produced using eight laser printers and 247 cartridges were collected to establish a dataset. Common manufacturers included HP, Canon, Lenovo, and Epson. After obtaining white-light images and three-dimensional profile images of printed characters, a morphological analysis was conducted by questioned document examiners (QDEs) using microscopy. Microscopic image features across a series of images were also extracted and analyzed using algorithms. Then, six high-dimensional reduction algorithms were used to obtain between- and within-printer variations as well as between- and within-cartridge variations. Finally, we conducted principal component analysis (PCA) and discriminant analysis. For 40 % of the samples, mixed discrimination analysis (MDA) and fixed discrimination analysis (FDA) were employed to predict the manufacturer, model and cartridge of laser printers used to produce the questioned printed document; the remaining 60 % samples comprised the training dataset. In the prediction of manufacturer, model and cartridge, our method achieved mean accuracies of 95.5 %, 97.5 %, and 90.2 %, respectively. Hence, this technique could reasonably aid in predicting the manufacturer, model, and cartridge of a laser printer, even if different cartridges are loaded into printers.

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来源期刊
Forensic science international
Forensic science international 医学-医学:法
CiteScore
5.00
自引率
9.10%
发文量
285
审稿时长
49 days
期刊介绍: Forensic Science International is the flagship journal in the prestigious Forensic Science International family, publishing the most innovative, cutting-edge, and influential contributions across the forensic sciences. Fields include: forensic pathology and histochemistry, chemistry, biochemistry and toxicology, biology, serology, odontology, psychiatry, anthropology, digital forensics, the physical sciences, firearms, and document examination, as well as investigations of value to public health in its broadest sense, and the important marginal area where science and medicine interact with the law. The journal publishes: Case Reports Commentaries Letters to the Editor Original Research Papers (Regular Papers) Rapid Communications Review Articles Technical Notes.
期刊最新文献
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