High-capacity reversible data hiding in encrypted 3D mesh models based on multi-MSB prediction

Reversible data hiding in encrypted domain (RDH-ED) technology performs content encryption to guarantee the privacy of original media and hide additional for multimedia management or access control. However, three dimensional (3D) model, it is still challenging improve embedding capacity under premise ensuring reversibility. This paper proposes an improvement RDH-ED method 3D models. Firstly, vertices are classified into “embedded set” “prediction based on odd-even property indices. Multiple most significant bit (multi-MSB) each vertex predicted adaptively marked model reserve room embedding. To further free up room, auxiliary information used extraction recovery can be compressed by entropy coding. Finally, correlation between two sets recover that were modified due Experimental results show proposed significantly improves compared with state-of-the-art methods.