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
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.