TY - JOUR
T1 - Detecting documents forged by printing and copying
AU - Shang, Shize
AU - Memon, Nasir
AU - Kong, Xiangwei
N1 - Funding Information:
The first and last authors were supported by the National Natural Science Foundation of China under Grant Number 61172109 and China Scholarship Council.
Publisher Copyright:
© 2014 Shang et al.; licensee Springer.
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
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U2 - 10.1186/1687-6180-2014-140
DO - 10.1186/1687-6180-2014-140
M3 - Article
AN - SCOPUS:84924810935
SN - 1687-6172
VL - 2014
SP - 1
EP - 13
JO - Eurasip Journal on Advances in Signal Processing
JF - Eurasip Journal on Advances in Signal Processing
IS - 1
M1 - 140
ER -