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Proceedings Paper

Scanner identification with extension to forgery detection
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Paper Abstract

Digital images can be obtained through a variety of sources including digital cameras and scanners. With rapidly increasing functionality and ease of use of image editing software, determining authenticity and identifying forged regions, if any, is becoming crucial for many applications. This paper presents methods for authenticating and identifying forged regions in images that have been acquired using flatbed scanners. The methods are based on using statistical features of imaging sensor pattern noise as a fingerprint for the scanner. An anisotropic local polynomial estimator is used for obtaining the noise patterns. A SVM classifier is trained for using statistical features of pattern noise for classifying smaller blocks of an image. This feature vector based approach is shown to identify the forged regions with high accuracy.

Paper Details

Date Published: 18 March 2008
PDF: 10 pages
Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190G (18 March 2008); doi: 10.1117/12.772048
Show Author Affiliations
Nitin Khanna, Purdue Univ. (United States)
George T. C. Chiu, Purdue Univ. (United States)
Jan P. Allebach, Purdue Univ. (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 6819:
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
Edward J. Delp; Ping Wah Wong; Jana Dittmann; Nasir D. Memon, Editor(s)

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