A Passive Approach for Detecting Image Splicing Based on Deep Learning and Wavelet Transform

Author:

Abd El-Latif Eman I.,Taha Ahmed,Zayed Hala H.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference33 articles.

1. Kumar, C.; Singh, A.K.; Kumar, P.: A recent survey on image watermarking techniques and its application in e-governance. Multimed. Tools Appl. 77(3), 3597–3622 (2017)

2. Qazi, T.; Hayat, K.; Khan, S.U.; Madani, S.A.; Khan, I.A.; Kołodziej, J.; Li, H.; Lin, W.; Yow, K.C.; Xu, C.-Z.: Survey on blind image forgery detection. J. IET Image Process. 7(7), 660–670 (2013)

3. Kapse, A.S.; Belokar, S.; Gorde, Y.; Rane, R.; Yewtkar, S.: Digital image security using digital watermarking. Int. Res. J. Eng. Technol. 5(3), 163–166 (2018)

4. Burvin, P.S.; Esther, J.M.: Analysis of digital image splicing detection. J. Comput. Eng. (IOSR-JCE) 16(2), 10–13 (2014)

5. Liua, W.; Wanga, Z.; Liua, X.; Zengb, N.; Liucd, Y.; Alsaadid, F.E.: A survey of deep neural network architectures and their applications. Neurocomputing 234(19), 11–26 (2017)

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