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.