Detecting documents forged by printing and copying

Shize Shang, Nasir Memon, Xiangwei Kong

Research output: Contribution to journalArticle

Abstract

This paper describes a method to distinguish documents produced by laser printers, inkjet printers, and electrostatic copiers, three commonly used document creation devices. The proposed approach can distinguish between documents produced by these sources based on features extracted from the characters in the documents. Hence, it can also be used to detect tampered documents produced by a mixture of these sources. We analyze the characteristics associated with laser/inkjet printers and electrostatic copiers and determine the signatures created by the different physical and technical processes involved in each type of printing. Based on the analysis of these signatures, we computed the features of noise energy, contour roughness, and average gradient. To the best of our knowledge, this is the first work to distinguish documents produced by laser printer, inkjet printer, and copier based on features extracted from individual characters in the documents. Experimental results show that this method has an average accuracy of 90% and works with JPEG compression.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalEurasip Journal on Advances in Signal Processing
Volume2014
Issue number1
DOIs
StatePublished - Sep 8 2014

Fingerprint

Copying
Printing
Lasers
Electrostatics
Surface roughness

Keywords

  • Average gradient
  • Contour roughness
  • Device type identification
  • Noise energy
  • Tampering detection

ASJC Scopus subject areas

  • Hardware and Architecture
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Detecting documents forged by printing and copying. / Shang, Shize; Memon, Nasir; Kong, Xiangwei.

In: Eurasip Journal on Advances in Signal Processing, Vol. 2014, No. 1, 08.09.2014, p. 1-13.

Research output: Contribution to journalArticle

@article{1704f556f0cb4e3fba72e6a44efce30e,
title = "Detecting documents forged by printing and copying",
abstract = "This paper describes a method to distinguish documents produced by laser printers, inkjet printers, and electrostatic copiers, three commonly used document creation devices. The proposed approach can distinguish between documents produced by these sources based on features extracted from the characters in the documents. Hence, it can also be used to detect tampered documents produced by a mixture of these sources. We analyze the characteristics associated with laser/inkjet printers and electrostatic copiers and determine the signatures created by the different physical and technical processes involved in each type of printing. Based on the analysis of these signatures, we computed the features of noise energy, contour roughness, and average gradient. To the best of our knowledge, this is the first work to distinguish documents produced by laser printer, inkjet printer, and copier based on features extracted from individual characters in the documents. Experimental results show that this method has an average accuracy of 90{\%} and works with JPEG compression.",
keywords = "Average gradient, Contour roughness, Device type identification, Noise energy, Tampering detection",
author = "Shize Shang and Nasir Memon and Xiangwei Kong",
year = "2014",
month = "9",
day = "8",
doi = "10.1186/1687-6180-2014-140",
language = "English (US)",
volume = "2014",
pages = "1--13",
journal = "Eurasip Journal on Advances in Signal Processing",
issn = "1687-6172",
publisher = "Springer Publishing Company",
number = "1",

}

TY - JOUR

T1 - Detecting documents forged by printing and copying

AU - Shang, Shize

AU - Memon, Nasir

AU - Kong, Xiangwei

PY - 2014/9/8

Y1 - 2014/9/8

N2 - This paper describes a method to distinguish documents produced by laser printers, inkjet printers, and electrostatic copiers, three commonly used document creation devices. The proposed approach can distinguish between documents produced by these sources based on features extracted from the characters in the documents. Hence, it can also be used to detect tampered documents produced by a mixture of these sources. We analyze the characteristics associated with laser/inkjet printers and electrostatic copiers and determine the signatures created by the different physical and technical processes involved in each type of printing. Based on the analysis of these signatures, we computed the features of noise energy, contour roughness, and average gradient. To the best of our knowledge, this is the first work to distinguish documents produced by laser printer, inkjet printer, and copier based on features extracted from individual characters in the documents. Experimental results show that this method has an average accuracy of 90% and works with JPEG compression.

AB - This paper describes a method to distinguish documents produced by laser printers, inkjet printers, and electrostatic copiers, three commonly used document creation devices. The proposed approach can distinguish between documents produced by these sources based on features extracted from the characters in the documents. Hence, it can also be used to detect tampered documents produced by a mixture of these sources. We analyze the characteristics associated with laser/inkjet printers and electrostatic copiers and determine the signatures created by the different physical and technical processes involved in each type of printing. Based on the analysis of these signatures, we computed the features of noise energy, contour roughness, and average gradient. To the best of our knowledge, this is the first work to distinguish documents produced by laser printer, inkjet printer, and copier based on features extracted from individual characters in the documents. Experimental results show that this method has an average accuracy of 90% and works with JPEG compression.

KW - Average gradient

KW - Contour roughness

KW - Device type identification

KW - Noise energy

KW - Tampering detection

UR - http://www.scopus.com/inward/record.url?scp=84924810935&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924810935&partnerID=8YFLogxK

U2 - 10.1186/1687-6180-2014-140

DO - 10.1186/1687-6180-2014-140

M3 - Article

AN - SCOPUS:84924810935

VL - 2014

SP - 1

EP - 13

JO - Eurasip Journal on Advances in Signal Processing

JF - Eurasip Journal on Advances in Signal Processing

SN - 1687-6172

IS - 1

ER -