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Superior SOM Neural Network based Minute Significant Watermark Generator and Detector System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 19 - Number 4 |
| Year of Publication: 2011 |
| Authors: N. Chenthalir Indra, E. Ramaraj |
10.5120/2352-3075
|
N. Chenthalir Indra, E. Ramaraj . Superior SOM Neural Network based Minute Significant Watermark Generator and Detector System. International Journal of Computer Applications. 19, 4 ( April 2011), 8-13. DOI=10.5120/2352-3075
Abstract
This paper suggests the Superior SOM (SSOM) based Minute Significant Watermark Generator & Detector (MSWG&D) system. RGB features of the host image are trained in different SSOM networks. Subsequent to SSOM training process, microscopic significant values are synthesized from host image and self-possessed as watermark values. Then these values are embedded into the high frequency sub band of Discrete Wavelet Transform (DWT). The Quality of invisible watermarking is proved by evaluating PSNR & Jaccard Similarity Ratio values between original and watermarked image. MSWG&D system is robust to JPEG compression and noise attacks. The experimental results prove that the strength of proposed watermarking system is ‘one more landmark’ in the watermarking techniques.
References
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