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Recoverable Tamper Proofing Technique for Image Authentication Using Irregular Sampling Coding

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Autonomic and Trusted Computing (ATC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4610))

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Abstract

Digital imagery is an important medium in information processing in the digital era. However, a major problem in information processing is that digital images can be forged easily. If this problem cannot be alleviated, the popularization of digital imagery will be decreased. Hence, in recent years, a few tamper proofing or image authentication techniques have been proposed to deal with this problem. In this paper, a new recoverable image authentication technique is proposed. Our method employs a very low bit-rated compression method called irregular sampling coding to compress the image. The compressed code is then randomly embedded into the original image using the digital watermarking technique. Since the image is highly compressed, it can be used to detect and recover the tampered-with information. Experimental results show that the proposed tamper proofing technique can effectively detect and recover the modified image. In addition, the experiments also show that the proposed technique is robust. Even though the image is 90%cropped or is highly compressed using JPEG, the quality of the recovered image is acceptable. The proposed method is therefore an effective, robust and recoverable tamper proofing technique.

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Bin Xiao Laurence T. Yang Jianhua Ma Christian Muller-Schloer Yu Hua

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© 2007 Springer-Verlag Berlin Heidelberg

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Hung, K.L., Chang, CC. (2007). Recoverable Tamper Proofing Technique for Image Authentication Using Irregular Sampling Coding. In: Xiao, B., Yang, L.T., Ma, J., Muller-Schloer, C., Hua, Y. (eds) Autonomic and Trusted Computing. ATC 2007. Lecture Notes in Computer Science, vol 4610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73547-2_35

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  • DOI: https://doi.org/10.1007/978-3-540-73547-2_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73546-5

  • Online ISBN: 978-3-540-73547-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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