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LWT-DCT based image hashing for image authentication via blind geometric correction

  • 1187: Recent Advances in Multimedia Information Security: Cryptography and Steganography
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Abstract

Image authentication based on robust image hashing has been paid large attention by researchers. However, most of the existing methods are unable to authenticate, if the image is processed through geometric transformations and tampered. In this paper, we have proposed a blind geometric correction approach, which eliminates the effect of geometric transformation, including rotation-scaling-translation (RST). We have incorporated Lifting Wavelet Transform (LWT) and Discrete Cosine Transform (DCT) to construct a short hash. Furthermore, an algorithm to generate an image map from the hash is proposed to detect the tampered regions. The main objective is to keep the hash length short with better performance, i.e., perceptually robust to content-preserving operations and image tampering detection. Based on the difference of image maps obtained from “source image” and “query images”, tampering regions have been localized. The proposed method can detect tampering, even if tampering and composite RST geometric transformations occur simultaneously, due to blind geometric correction. The experimental results show that the proposed image authentication method outperforms the state-of-the-art techniques.

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Acknowledgements

The author would like to thank all the Ph.D. scholars of Speech and Image Processing Laboratory and National Institute of Technology Silchar, India, for offering help and vital facilities for doing this work.

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Authors and Affiliations

  1. Speech and Image Processing Group, Electronics and Communication Engineering Department, National Institute of Technology, 788010, Assam, India

    Ram Kumar Karsh

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  1. Ram Kumar Karsh
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Correspondence to Ram Kumar Karsh.

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Appendices

Appendix 1 DCT matrix

figure e

where \({\mathbf{T}}(u,v)\) has been obtained as \({\mathbf{T}}\left(u,v\right)=\left\{\begin{array}{*{20}c}\sqrt{1/m}\quad\ ; u=0 and 0\le v\le m-1 \\ \sqrt{2/m} cos\left[\frac{\left(2v+1\right)\pi u}{2 m}\right] ;1\le u\le m-1 and 0\le v\le m-1\end{array}\right.\)

Appendix 2 Zigzag ordering and invers-ordering

Fig. 9
figure 9

Diagram of zigzag scanning

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The zigzag order is obtainedas per arrow direction shown in Fig. 9, given below.

figure f

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Karsh, R.K. LWT-DCT based image hashing for image authentication via blind geometric correction. Multimed Tools Appl 82, 22083–22101 (2023). https://doi.org/10.1007/s11042-022-13349-2

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