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

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dc.contributor.authorEr, Füsun
dc.contributor.authorYalman, Yıldıray
dc.date.accessioned2026-02-08T15:04:48Z
dc.date.available2026-02-08T15:04:48Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThis 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
dc.identifier.doi10.38088/jise.1135756
dc.identifier.endpage247
dc.identifier.issn2602-4217
dc.identifier.issue2
dc.identifier.startpage233
dc.identifier.urihttps://doi.org/10.38088/jise.1135756
dc.identifier.urihttps://hdl.handle.net/20.500.12885/4191
dc.identifier.volume6
dc.language.isoen
dc.publisherBursa Teknik Üniversitesi
dc.relation.ispartofJournal of Innovative Science and Engineering
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20260207
dc.subjectEngineering
dc.subjectMühendislik
dc.titleAn Application of Non-Dominated Sorting Genetic Algorithm for Reversible Data Hiding Based on Histogram Shifting in Neuroimages
dc.typeArticle

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