Localization and text sequence restoration using noise pixels in binary document image watermarking

N. B. Puhan; Anthony Tung Shuen Ho; Farook Sattar

doi:10.1117/1.3143184

1 April 2009 Localization and text sequence restoration using noise pixels in binary document image watermarking

N. B. Puhan, Anthony Tung Shuen Ho, Farook Sattar

Author Affiliations +

Journal of Electronic Imaging, Vol. 18, Issue 2, 023012 (April 2009). https://doi.org/10.1117/1.3143184

Abstract

We propose a new method for tamper localization and restoration using noise pixels in binary document images. For such images, it is difficult to find a sufficient number of low-distortion pixels in individual blocks with blind detection property. Also, a perceptual watermark cannot be embedded in white regions of the document image, making such regions insecure against hostile attacks. An erasable watermark is embedded in each block of the document image independently. The embedding process introduces some background noise. However, the content in the document can be interpreted by the user, because human vision has the inherent capability to recognize various patterns in the presence of noise. If authenticity is verified for the content of each block, the exact copy of original image is restored at the blind detector for further use and analysis. Experimental results show that an erasable watermark of necessary data length can be embedded in individual blocks to attain effective localization and restoration capability. Using the proposed method, it is possible to restore the original text sequence in text document images after multiple alterations like text deletion, insertion, substitution, and block swapping.

©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

N. B. Puhan, Anthony Tung Shuen Ho, and Farook Sattar "Localization and text sequence restoration using noise pixels in binary document image watermarking," Journal of Electronic Imaging 18(2), 023012 (1 April 2009). https://doi.org/10.1117/1.3143184

Published: 1 April 2009

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