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Proceedings Paper

Robust scanner identification based on noise features
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Paper Abstract

A large portion of digital image data available today is acquired using digital cameras or scanners. While cameras allow digital reproduction of natural scenes, scanners are often used to capture hardcopy art in more controlled scenarios. This paper proposes a new technique for non-intrusive scanner model identification, which can be further extended to perform tampering detection on scanned images. Using only scanned image samples that contain arbitrary content, we construct a robust scanner identifier to determine the brand/model of the scanner used to capture each scanned image. The proposed scanner identifier is based on statistical features of scanning noise. We first analyze scanning noise from several angles, including through image de-noising, wavelet analysis, and neighborhood prediction, and then obtain statistical features from each characterization. Experimental results demonstrate that the proposed method can effectively identify the correct scanner brands/models with high accuracy.

Paper Details

Date Published: 27 February 2007
PDF: 11 pages
Proc. SPIE 6505, Security, Steganography, and Watermarking of Multimedia Contents IX, 65050S (27 February 2007); doi: 10.1117/12.704688
Show Author Affiliations
Hongmei Gou, Univ. of Maryland/College Park (United States)
Ashwin Swaminathan, Univ. of Maryland/College Park (United States)
Min Wu, Univ. of Maryland/College Park (United States)

Published in SPIE Proceedings Vol. 6505:
Security, Steganography, and Watermarking of Multimedia Contents IX
Edward J. Delp III; Ping Wah Wong, Editor(s)

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