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Journals / Journal of Innovative Science and Engineering / 2022 / Cilt: 6 - Sayı: 2

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

Füsun ER
Yıldıray YALMAN
Pages
233–247
Publication Date
2022-12-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The experimental results show that the proposed method is better than its counterparts

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
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Key Findings & Data: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.
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Conclusion & Impact:The experimental results show that the proposed method is better than its counterparts
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Genetic algorithm · information security · magnetic resonance imaging

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

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Cite This Article

ER, F., YALMAN, Y. (2022). An Application of Non-Dominated Sorting Genetic Algorithm for Reversible Data Hiding Based on Histogram Shifting in Neuroimages. Journal of Innovative Science and Engineering, Cilt: 6 - Sayı: 2, 233–247. https://ajindex.com/articles/882038

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