Near infrared hyperspectral imaging for forensic analysis of document forgery

被引:67
|
作者
Silva, Carolina S. [1 ]
Pimentel, Maria Fernanda [2 ]
Honorato, Ricardo S. [3 ]
Pasquini, Celio [4 ]
Prats-Montalban, Jose M. [5 ]
Ferrer, Alberto [5 ]
机构
[1] Univ Fed Pernambuco, Dept Quim Fundamental, BR-50740521 Recife, PE, Brazil
[2] Univ Fed Pernambuco, Dept Engn Quim, BR-50740521 Recife, PE, Brazil
[3] Superintendencia Reg Pernambuco, Policia Fed, Brazil
[4] Univ Estadual Campinas, Inst Quim, Campinas, SP, Brazil
[5] Univ Politecn Valencia, Dept Estadist & Invest Operat Aplicadas & Calidad, Valencia, Spain
关键词
BALLPOINT PEN INKS; MULTIVARIATE CURVE RESOLUTION; PRINCIPAL COMPONENT ANALYSIS; CLASSIFICATION; SPECTROSCOPY; SEPARATION; TOOL;
D O I
10.1039/c4an00961d
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Hyperspectral images in the near infrared range (HSI-NIR) were evaluated as a nondestructive method to detect fraud in documents. Three different types of typical forgeries were simulated by (a) obliterating text, (b) adding text and (c) approaching the crossing lines problem. The simulated samples were imaged in the range of 928-2524 nm with spectral and spatial resolutions of 6.3 nm and 10 gm, respectively. After data pre-processing, different chemometric techniques were evaluated for each type of forgery. Principal component analysis (PCA) was performed to elucidate the first two types of adulteration, (a) and (b). Moreover, Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) was used in an attempt to improve the results of the type (a) obliteration and type (b) qdding text problems. Finally, MCR-ALS and Partial Least Squares Discriminant Analysis (PLS-DA), employed as a variable selection tool, were used to study the type (c) forgeries, i.e. crossing lines problem. Type (a) forgeries (obliterating text) were successfully identified in 43% of the samples using both the chemometric methods (PCA and MCR-ALS). Type (b) forgeries (adding text) were successfully identified in 82% of the samples using both the methods (PCA and MCR-ALS). Finally, type (c) forgeries (crossing lines) were successfully identified in 85% of the samples. The results demonstrate the potential of HSI-NIR associated with chemometric tools to support document forgery identification.
引用
收藏
页码:5176 / 5184
页数:9
相关论文
共 50 条
  • [1] Forensic Inspection of Document Using Visible and Near-Infrared Spectral Imaging
    Huang Wei
    Wang Guiqiang
    Xu Xiaojing
    Yu Tao
    Yang Zhicheng
    OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY, 2010, 7850
  • [2] Detection of residues from explosive manipulation by near infrared hyperspectral imaging: A promising forensic tool
    Angeles Fernandez de la Ossa, Ma
    Amigo, Jose Manuel
    Garcia-Ruiz, Carmen
    FORENSIC SCIENCE INTERNATIONAL, 2014, 242 : 228 - 235
  • [3] iVision HHID: Handwritten hyperspectral images dataset for benchmarking hyperspectral imaging-based document forensic analysis
    Ul Islam, Ammad
    Khan, Muhammad Jaleed
    Asad, Muhammad
    Khan, Haris Ahmad
    Khurshid, Khurram
    DATA IN BRIEF, 2022, 41
  • [4] An efficient technique for detecting document forgery in hyperspectral document images
    EL Abady, Naglaa F.
    Zayed, Hala H.
    Taha, Mohamed
    ALEXANDRIA ENGINEERING JOURNAL, 2023, 85 : 207 - 217
  • [5] Localized Forgery Detection in Hyperspectral Document Images
    Luo, Zhipei
    Shafait, Paisal
    Mian, Ajmal
    2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), 2015, : 496 - 500
  • [6] Qualitative analysis for sweetness classification of longan by near infrared hyperspectral imaging
    Sahachairungrueng, W.
    Teerachaichayut, S.
    INTERNATIONAL CONFERENCE ON ENGINEERING, APPLIED SCIENCES AND TECHNOLOGY 2019, 2019, 639
  • [7] Hyperspectral Cathodoluminescence Imaging and Analysis Extending from Ultraviolet to Near Infrared
    MacRae, C. M.
    Wilson, N. C.
    Torpy, A.
    Davidson, C. J.
    MICROSCOPY AND MICROANALYSIS, 2012, 18 (06) : 1239 - 1245
  • [8] Single-kernel maize analysis by near-infrared hyperspectral imaging
    Cogdill, RP
    Hurburgh, CR
    Rippke, GR
    TRANSACTIONS OF THE ASAE, 2004, 47 (01): : 311 - 320
  • [9] Near-infrared hyperspectral imaging for quality analysis of agricultural and food products
    Singh, C. B.
    Jayas, D. S.
    Paliwal, J.
    White, N. D. G.
    SENSING FOR AGRICULTURE AND FOOD QUALITY AND SAFETY II, 2010, 7676
  • [10] Near Infrared Hyperspectral Imaging System for Root Phenotyping
    Arnold, Thomas
    Leitner, Raimund
    Bodner, Gernot
    SENSING FOR AGRICULTURE AND FOOD QUALITY AND SAFETY IX, 2017, 10217