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DOI: 10.14569/SpecialIssue.2011.010110
PDF

Fine Facet Digital Watermark (FFDW) Mining From The Color Image Using Neural Networks

Author 1: N Chenthalir Indra
Author 2: Dr. E . Ramaraj

International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: On hand watermark methods employ selective Neural Network techniques for watermark embedding efficiently. Similarity Based Superior Self Organizing Maps (SBS_SOM) a neural network algorithm for watermark generation. Host image is learned by the SBS_SOM neurons and the very fine RGB feature values are mined as digital watermark. Discrete Wavelet Transform (DWT) is used for watermark entrench. Similarity Ratio and PSNR values prove the temperament of the Fine Facet Digital Watermark (FFDW). The Proposed system affords inclusive digital watermarking system.

Keywords: Similarity based Superior SOM; Discrete Wavelet Transform; Digital watermark; embedding; PSNR.

N Chenthalir Indra and Dr. E . Ramaraj, “Fine Facet Digital Watermark (FFDW) Mining From The Color Image Using Neural Networks” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011. http://dx.doi.org/10.14569/SpecialIssue.2011.010110

@article{Indra2011,
title = {Fine Facet Digital Watermark (FFDW) Mining From The Color Image Using Neural Networks},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis}
doi = {10.14569/SpecialIssue.2011.010110},
url = {http://dx.doi.org/10.14569/SpecialIssue.2011.010110},
year = {2011},
publisher = {The Science and Information Organization},
volume = {1},
number = {1},
author = {N Chenthalir Indra and Dr. E . Ramaraj},
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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