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CRP2-VCS: Contrast-Oriented Region-based Progressive Probabilistic Visual Cryptography Schemes

aut.relation.endpage1
aut.relation.journalIEEE Transactions on Circuits and Systems for Video Technology
aut.relation.startpage1
dc.contributor.authorWu, Xiaotian
dc.contributor.authorSong, Bofan
dc.contributor.authorFang, Jia
dc.contributor.authorYan, WeiQi
dc.contributor.authorPeng, Qing-Yu
dc.date.accessioned2025-11-03T23:23:50Z
dc.date.available2025-11-03T23:23:50Z
dc.date.issued2025
dc.description.abstractMost visual cryptography schemes (VCSs) are condition-oriented which implies their designs focus on satisfying the contrast and security conditions in VCS. In this paper, we explore a new architecture of VCS: contrast-oriented region-based progressive probabilistic VCS (CRP2-VCS). The term contrast-oriented indicates the optimality of multi-contrast is taken into consideration when producing shadows. First of all, new requirements for CRP2-VCS, described by probabilities, are introduced. As a non-interference requirement is proposed, the secret interference problem in existing region-based progressive VCS can be avoided. Then, a construction of CRP2-VCS based on a multi-contrast-maximizing model is provided. The multi-contrast-maximizing problem is essentially a probabilistic VCS model that fuses region-based sharing, multi-contrast optimization, and general access structure (GAS) together. Finally, a Max-Min based technique is adopted to solve the multi-objective optimization problem. Moreover, to further boost the visual quality, the proposed method is extended to allow employing XOR operation for image recovery. Experimental results and comparisons are demonstrated to show the effectiveness and advantages, such as optimal visual quality, non-expansible shadow and GAS sharing policy, are provided by the proposed technique.
dc.identifier.citationIEEE Transactions on Circuits and Systems for Video Technology, ISSN: 1051-8215 (Print); 1558-2205 (Online), Institute of Electrical and Electronics Engineers (IEEE), 1-1. doi: 10.1109/tcsvt.2025.3532454
dc.identifier.doi10.1109/tcsvt.2025.3532454
dc.identifier.issn1051-8215
dc.identifier.issn1558-2205
dc.identifier.urihttp://hdl.handle.net/10292/20049
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urihttps://ieeexplore.ieee.org/document/10848184
dc.rights© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accessrightsOpenAccess
dc.subject0801 Artificial Intelligence and Image Processing
dc.subject0906 Electrical and Electronic Engineering
dc.subjectArtificial Intelligence & Image Processing
dc.subject4006 Communications engineering
dc.subject4009 Electronics, sensors and digital hardware
dc.subject4603 Computer vision and multimedia computation
dc.titleCRP2-VCS: Contrast-Oriented Region-based Progressive Probabilistic Visual Cryptography Schemes
dc.typeJournal Article
pubs.elements-id586663

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