Effect of Scanner Resolution and Character Selection on Source Printer Identification

Aronoff, Jason S.; Simske, Steven J.

doi:10.2352/j.imagingsci.technol.2011.55.5.050602

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…The rotation angle θ 0 is determined as θ 0 ¼ arg maxfρ½P 1 ðθ − θ 0 ; rÞ; P 2 ðθ; rÞg; (9) where ρðP 1 ; We translate the scanned character image with a specified angle range and calculate the correlation coefficient between the translated character and reference character images.…”

Section: Reference Document Image Restoration By Ocr;mentioning

confidence: 99%

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Document forgery detection using distortion mutation of geometric parameters in characters

Shang

Kong

You

2015

J. Electron. Imaging

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Tampering related to document forgeries is often accomplished by copy-pasting or add-printing. These tampering methods introduce character distortion mutation in documents. We present a method of exposing document forgeries using distortion mutation of geometric parameters. We estimate distortion parameters, which consist of translation and rotation distortions, through image matching for each character. Detection of tampered characters with distortion mutation occurs based on a distortion probability, which is calculated from character distortion parameters. The introduction of a visualized probability map describes the degree of distortion mutation for a full page. The proposed method exposes the forgeries based on individual characters and applies to English and Chinese document examinations. Experimental results demonstrate the effectiveness of our method on low JPEG compression quality and low resolution. Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 023008-2 Mar∕Apr 2015 • Vol. 24(2) Shang, Kong, and You: Document forgery detection using distortion mutation of geometric parameters in characters Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 023008-4 Mar∕Apr 2015 • Vol. 24(2) Shang, Kong, and You: Document forgery detection using distortion mutation of geometric parameters in characters Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 023008-5 Mar∕Apr 2015 • Vol. 24(2) Shang, Kong, and You: Document forgery detection using distortion mutation of geometric parameters in characters Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 023008-6 Mar∕Apr 2015 • Vol. 24(2) Shang, Kong, and You: Document forgery detection using distortion mutation of geometric parameters in characters Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 023008-8 Mar∕Apr 2015 • Vol. 24(2) Shang, Kong, and You: Document forgery detection using distortion mutation of geometric parameters in characters Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/15/2015 Terms of Use: http://spiedl.org/terms

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Section: Reference Document Image Restoration By Ocr;mentioning

confidence: 99%

“…This method consists of printer identification, 1-8 scanner identification, [9][10][11][12] and document forgery detection. Forensic analysis utilizing a computer and flatbed scanner is a viable option.…”

Section: Introductionmentioning

confidence: 99%

Document forgery detection using distortion mutation of geometric parameters in characters

Shang

Kong

You

2015

J. Electron. Imaging

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“…Although document forensics works based on scanned images, the methods are significantly different. Recent research in document forensics has focused on printer identification [2][3][4][5][6][7][8], forgery detection [9][10][11][12], and scanner identification [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Detecting documents forged by printing and copying

Shang

Memon

Kong

2014

EURASIP J. Adv. Signal Process.

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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.

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Effect of Scanner Resolution and Character Selection on Source Printer Identification

Cited by 2 publications

References 9 publications

Document forgery detection using distortion mutation of geometric parameters in characters

Document forgery detection using distortion mutation of geometric parameters in characters

Detecting documents forged by printing and copying

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