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An Intelligent Blind Semi-fragile Watermarking Scheme for Effective Authentication and Tamper Detection of Digital Images Using Curvelet Transforms

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Advances in Signal Processing and Intelligent Recognition Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 425))

Abstract

A novel intelligent semi-fragile watermarking scheme for authentication and tamper detection of digital images is proposed in this paper. This watermarking scheme involves embedding and extraction of the quantized first level Discrete Curvelet Transform (DCLT) coarse coefficients. The amount of quantization of the first level coarse DCLT coefficients of the input image is decided intelligently based on the energy contribution of the coefficients. At the receiver side, the extracted and generated first level coarse DCLT coefficients of the watermarked image is divided into blocks of uniform size. A feature similarity index value between each block of extracted and generated coefficients is compared and if the difference exceeds threshold, the block is marked as tampered. The watermarking scheme is blind and does not require any additional information to identify authenticity of the watermarked image. Experiments are conducted rigorously and the results reveal that the proposed method is robust than the existing method [1]. Better accuracy in localizing tampered regions is achieved compared to method [1].

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Authors and Affiliations

  1. Department of CSE, JNN College of Engineering, Chennai, India

    K. R. Chetan & S. Nirmala

Authors
  1. K. R. Chetan
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  2. S. Nirmala
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Corresponding author

Correspondence to K. R. Chetan .

Editor information

Editors and Affiliations

  1. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. Department of Electrical, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  4. Providence University, Taichung, Taiwan

    Kuan-Ching Li

  5. Computer Engineering Department, Vladimir State University, Vladimir Region, Russia

    Sergey Mosin

  6. School of Electrical, Nanyang Technological University, Singapore, Singapore

    Maode Ma

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Chetan, K.R., Nirmala, S. (2016). An Intelligent Blind Semi-fragile Watermarking Scheme for Effective Authentication and Tamper Detection of Digital Images Using Curvelet Transforms. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_17

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  • DOI: https://doi.org/10.1007/978-3-319-28658-7_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28656-3

  • Online ISBN: 978-3-319-28658-7

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