An Application of Non-Dominated Sorting Genetic Algorithm for Reversible Data Hiding Based on Histogram Shifting in Neuroimages

Abstract

This paper presents an application of a multi-objective non-dominated sorting genetic algorithm with a modified chromosome encoding for histogram shifting-based multiple reversible data hiding scheme in neuroimages which aims to minimize distortion and maximize capacity. The modified chromosomes encoding scheme is designed according to the zero-bin characteristic of the intensity histogram of the structural magnetic resonance imaging scans of the human brain. A detailed experimental study has been carried out for assessing the effect of non-dominated sorting for multi-objective optimization compared to Euclidian distance, the convenience of modified chromosome encoding scheme for medical images compared to non-medical images. The performance of the proposed method has been measured in terms of the peak signal-to-noise ratio (PSNR) for image quality and the bits per pixel (bpp) for capacity assessments. The experimental results show that the proposed method is better than its counterparts

Keywords

• genetic algorithm
• information security
• magnetic resonance imaging
• reversible data hiding