A Reversible Data Hiding Scheme for 3D Polygonal Models Based on Histogram Shifting with High Embedding Capacity
Reversibility is the ability to recover the stego media back to the cover media without any error after correctly extracting the secret message. This study proposes a reversible data hiding scheme for 3D polygonal models based on histogram shifting. Specifically, the histogram construction is based on the geometric similarity between neighboring vertices. The distances between the neighboring vertices in a 3D model with some point in the 3D space are usually similar, especially for a high-resolution 3D model. Therefore, the difference between the above distances of the neighboring vertices has a small value for a high probability. This study uses the modified breadth-first search to traverse each vertex once in a sequential order and determine the unique referencing neighbor for each vertex. The histogram is then constructed based on the normalized distance difference of neighboring vertices. This approach significantly increases embedding capacity. Experimental results show that the proposed algorithm can achieve higher embedding capacity than existing algorithms while still maintaining acceptable model distortion. This algorithm also provides greater robustness against similarity transformation attacks and vertex reordering attacks. The proposed technique is feasible for 3D reversible data hiding.
reversibility data hiding 3d polygonal models histogram shifting breadth-first search