18 March 2008 Scanner identification with extension to forgery detection
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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.
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Nitin Khanna, Nitin Khanna, George T. C. Chiu, George T. C. Chiu, Jan P. Allebach, Jan P. Allebach, Edward J. Delp, Edward J. Delp, } "Scanner identification with extension to forgery detection", Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190G (18 March 2008); doi: 10.1117/12.772048; https://doi.org/10.1117/12.772048
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