LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Evaluation of bioinspired algorithms for image optimization

Abstract. Steganography is a technique for concealing sensitive information behind a specific media source, such as an image, audio, or video file, in such a way that the concealed data… Click to show full abstract

Abstract. Steganography is a technique for concealing sensitive information behind a specific media source, such as an image, audio, or video file, in such a way that the concealed data are invisible to everyone. Many algorithms have been developed to optimize this process for better output. We aim to identify the different optimization algorithms used in image steganography after embedding the data to improve the resilience, visibility, and payload carrying capacity. Additionally, we highlight several bioinspired algorithms, including particle swarm optimization, ant colony optimization, firefly optimization, and artificial bee colony optimization, and evaluate through performance measures such as peak signal-to-noise ratio (PSNR) and mean square error (MSE). The performance metrics generated from the collected data indicate that the firefly method produced a higher PSNR and a lower MSE, namely 72.42 dB and 0.13, respectively. The methods are evaluated in terms of their ability for data embedding, robustness, and imperceptibility.

Keywords: image optimization; evaluation bioinspired; bioinspired algorithms; image; optimization; algorithms image

Journal Title: Journal of Electronic Imaging
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.