A new watermarking approach based on probabilistic neural network in wavelet domain

  • Authors:

  • Xian-Bin Wen;Hua Zhang;Xue-Quan Xu;Jin-Juan Quan

  • Affiliations:

  • Tianjin Univ. of Technology, School of Comp. Sci. and Technol., 300191, Tianjin, People’s Republic of China and Tianjin Key Lab. of Intelligence Computing and Novel Software Technology, 300 ...;Tianjin Univ. of Technology, School of Comp. Sci. and Technol., 300191, Tianjin, People’s Republic of China and Tianjin Key Lab. of Intelligence Computing and Novel Software Technology, 300 ...;Tianjin Univ. of Technology, School of Comp. Sci. and Technol., 300191, Tianjin, People’s Republic of China and Tianjin Key Lab. of Intelligence Computing and Novel Software Technology, 300 ...;Tianjin Univ. of Technology, School of Comp. Sci. and Technol., 300191, Tianjin, People’s Republic of China and Tianjin Key Lab. of Intelligence Computing and Novel Software Technology, 300 ...

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Bio-Inspired Information Hiding; Guest editors: Jeng-Shyang Pan, Ajith Abraham
  • Year:
  • 2008

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Abstract

A novel scheme of digital image watermarking based on the combination of dual-tree wavelet transform (DTCWT) and probabilistic neural network is proposed in this paper. Firstly, the original image is decomposed by DTCWT, and then the watermark bits are added to the selected coefficients blocks. Because of the learning and adaptive capabilities of neural networks, the trained neural networks can recover the watermark from the watermarked images. Experimental results show that the proposed scheme has good performance against several attacks.