Particle Swarm Bacterial Foraging Optimization method for Enhanced digital image watermarking system for data security comparison with Genetic algorithm

Abstract

The primary objective of this study is to enhance the data security of digital image watermarking systems through the application of Bacterial Foraging with Particle Swarm Optimization (BF-PSO) and compare Peak Signal Noise Ratio (PSNR) with a Genetic algorithm (GA). The dataset in this paper utilizes 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. Bacterial foraging with particle swarm optimization (BF-PSO) and while number of samples (N=10) and Genetic algorithm (GA), where number of samples (N=10) are taken into consideration are used to analyze the digital image watermarking system with improved PSNR. The novel Bacterial Foraging with Particle Swarm Optimization (BF-PSO) has 58.30 higher PSNR when compared to the PSNR of Genetic algorithm (GA) is 40.55. The significance level of the study is p<0.05, or p=0.037. Bacterial Foraging with Particle Swarm Optimization (BF-PSO) in comparison to Genetic algorithm (GA) yields superior results in Peak Signal Noise Ratio (PSNR) when it comes to improving digital image watermarking systems and ensuring the safety of the data.