Enhanced Digital Image Watermarking System using Manta Ray Foraging Comparison with Bi-directional ELM for Data Security
Deepthi Pula, R. Puviarasi · 2023
The main objective of this study is to enhance data security in digital image watermarking systems using Manta Ray Foraging Optimization (MRFO) and compare Peak Signal-to-Noise Ratio (PSNR) with Bidirectional ELM (BELM). The dataset in this paper utilises the publicly available Kaggle database. The sample size for analysing the data security in a digital image watermarking system with enhanced PSNR was 20 (Group$1=10$and Group 2$=10)$and calculations were conducted using G-power 0.8 alpha and beta values of 0.05 and 0.2 and a 95% confidence interval. The evaluation of the digital image watermarking system with increased PSNR is performed by Manta Ray Foraging Optimization (BLEM) and whereas number of samples$(\mathrm{N}=10)$and Bi-directional ELM (BELM) where number of samples$(\mathrm{N}=10)$. The PSNR of Manta Ray Foraging Optimization (MRFO) is 60.30 percent greater than that of Bi-directional ELM (BELM) which is 44.50 percent. The significance level of the study is$\mathrm{p} < 0.05$or$\mathrm{p}=0.025$. Manta Ray Foraging Optimization (MRFO) achieves a higher PSNR than Bi-directional ELM (BELM) when it relates to improving digital image watermarking systems and protecting the data.