An Optimized Zero-Watermarking Technique Based on SFL Algorithm

Zero-watermarking techniques are the most interesting types of digital watermarking, especially, in legal and medical images. These techniques are work on extracting the most important features from images for creating secret watermarks without any alteration in the original images. In order to extract the robust features which are able to resist various types of attacks, the optimization algorithms should be used. In this paper, appropriate locations for extracting the most important features from the singular-value decomposition (SVD) of a digital image are selected depending on Shuffled Frog Leaping (SFL) algorithm. The analysis of the implementation presents that the proposed technique is highly robust under various attacks, where the values of normalized cross-correlation (NCC) of the selected attacks are utilized a fitness function for the SFL algorithm.