Scanner identification using sensor pattern noise

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Author

Nitin Khanna and Aravind K. Mikkilineni and George T. C. Chiu and Jan P. Allebach and Edward J. Delp

Entry type

conference

Abstract

Digital images can be captured or generated by a variety of sources including digital cameras and scanners. In many cases it is important to be able to determine the source of a digital image. This paper presents methods for authenticating images that have been acquired using flatbed desktop scanners. The method is based on using the pattern noise of the imaging sensor as a fingerprint for the scanner, similar to methods that have been reported for identifying digital cameras. To identify the source scanner of an image a reference pattern is estimated for each scanner and is treated as a unique fingerprint of the scanner. An anisotropic local polynomial estimator is used for obtaining the reference patterns. To further improve the classification accuracy a feature vector based approach using an SVM classifier is used to classify the pattern noise. This feature vector based approach is shown to achieve a high classification accuracy.

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Date

2007 – 02

Booktitle

Proceedings of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents IX

Editor

Edward J. Delp III and Ping Wah Wong

Journal

Proceedings of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents IX

Key alpha

Scanner_identification_using_sensor_pattern_noise

Number

Pages

65051K

Publisher

SPIE

Volume

6505

Affiliation

Purdue University

Publication Date

2007-02-01

Keywords

digital forensics, imaging sensor classification, flatbed scanner, sensor noise, scanner forensics

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@Conference{ Scanner_identification_using_sensor_pattern_noise,
	title = "Scanner identification using sensor pattern noise",
	author = "Nitin Khanna and Aravind K. Mikkilineni and George T. C. Chiu and Jan P. Allebach and Edward J. Delp",
	year = "2007",
	month = "02",
	booktitle = "Proceedings of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents IX",
	editor = "Edward J. Delp III and Ping Wah Wong",
	journal = "Proceedings of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents IX",
	number = "1",
	pages = "65051K",
	publisher = "SPIE",
	volume = "6505",
	abstract = "Digital images can be captured or generated by a variety of sources including digital cameras and scanners. In
many cases it is important to be able to determine the source of a digital image. This paper presents methods for
authenticating images that have been acquired using flatbed desktop scanners. The method is based on using the
pattern noise of the imaging sensor as a fingerprint for the scanner, similar to methods that have been reported
for identifying digital cameras. To identify the source scanner of an image a reference pattern is estimated for
each scanner and is treated as a unique fingerprint of the scanner. An anisotropic local polynomial estimator is
used for obtaining the reference patterns. To further improve the classification accuracy a feature vector based
approach using an SVM classifier is used to classify the pattern noise. This feature vector based approach is
shown to achieve a high classification accuracy.",
	affiliation = "Purdue University",
	keywords = "digital forensics, imaging sensor classification, flatbed scanner, sensor noise, scanner forensics",
}