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Main Authors: Tang, Yun, Cheng, Lulu, Lyv, Wanli, Yin, Zhaoxia
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2211.02801
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author Tang, Yun
Cheng, Lulu
Lyv, Wanli
Yin, Zhaoxia
author_facet Tang, Yun
Cheng, Lulu
Lyv, Wanli
Yin, Zhaoxia
contents Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further improve the capacity, a RDH-ED method is proposed based on the topology of the 3D mesh models, which divides the vertices into two parts: embedding set and prediction set. And after integer mapping, the embedding ability of the embedding set is calculated by the prediction set. It is then passed to the data hider for embedding additional data. Finally, the additional data and the original models can be extracted and recovered respectively by the receiver with the correct keys. Experiments declare that compared with the existing methods, this method can obtain the highest embedding capacity.
format Preprint
id arxiv_https___arxiv_org_abs_2211_02801
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle High Capacity Reversible Data Hiding for Encrypted 3D Mesh Models Based on Topology
Tang, Yun
Cheng, Lulu
Lyv, Wanli
Yin, Zhaoxia
Multimedia
Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further improve the capacity, a RDH-ED method is proposed based on the topology of the 3D mesh models, which divides the vertices into two parts: embedding set and prediction set. And after integer mapping, the embedding ability of the embedding set is calculated by the prediction set. It is then passed to the data hider for embedding additional data. Finally, the additional data and the original models can be extracted and recovered respectively by the receiver with the correct keys. Experiments declare that compared with the existing methods, this method can obtain the highest embedding capacity.
title High Capacity Reversible Data Hiding for Encrypted 3D Mesh Models Based on Topology
topic Multimedia
url https://arxiv.org/abs/2211.02801