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  • 标题:A Novel Approach using Full Counterpropagation�Neural Network for Watermarking
  • 本地全文:下载
  • 作者:Ashish Bansal ; Dr. Sarita Singh Bhadauria
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2010
  • 卷号:2
  • 期号:2
  • 页码:289-296
  • 出版社:Engg Journals Publications
  • 摘要:Digital Watermarking offers techniques to hide watermarks into digital content to protect it from illegal copy or reproduction. Existing techniques based on spatial and frequency domain suffer from the problems of low Peak Signal to Noise Ratio (PSNR) of watermark and image quality degradation in varying degree. Earlier technique based on Full Counterpropagation Neural Network (FCNN) used the concept of embedding the watermark into synapses of neural net rather than the cover image to improve PSNR of watermark and to prevent image quality degradation. However, problems like "Proprietary neural net" and "sure win" still exist as explained in this work. This paper is an attempt to uncover and solve these problems. FCNN can be practically employed to obtain a successful watermarking scheme with better time complexity, higher capacity and higher PSNR with the suggested modifications.
  • 关键词:Digital watermark; neural net; FCNN; Discrete Cosine Transform(DCT).
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