An Improved Scheme for Digital Watermarking Using Functional Link Artificial Neural Network
Abstract
The present study proposes a novel technique for copyright protection by utilizing digital watermarking of Images. The watermark is embedded and detected by using Functional Link Artificial Neural Network (FLANN) and Discrete Cosine Transform (DCT). The exhaustive simulation results of the proposed scheme show improved performance over the existing methods in all cases, i.e. when the watermarked image is subjected to compression, cropping, sharpening, blurring and noise. Comparative analysis with an existing neural approach shows the superiority of the proposed scheme of computational complexity and performance.
DOI: https://doi.org/10.3844/jcssp.2005.169.174
Copyright: © 2005 Banshidhar Majhi and Hasan Shalabi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Digital Watermarking
- One-way Hash Function
- FLANN
- MLP
- DCT
- JPEG Compression
- Cropping