Projection Sampling of Point Clouds and a Novel High-Capacity 3D Information Hiding Method

Aiming at the problems of long synchronization time and instability issues in the existing 3D information hiding algorithms, a novel 3D projection sampling strategy for 3D point cloud data is proposed. Projecting all vertices onto the XOY plane, and the number of sampled vertex is controlled by adjusting the resolution of the projection surface, and the vertex synchronization is realized by regular access to the sampled points. Based on this strategy, a novel information hiding approach is proposed for 3D point cloud data. Secret data is embedded into the Z-axis coordinate and the three color components at the same time. Due to the fixed X and Y-axis coordinates, the stability of vertex synchronization is ensured when large-capacity data is embedded. The host model is not needed when extracting the secret data, so it is a blind extraction. Substantial simulation experiments are conducted through Matlab by using public 3D data, such as several animals and a human face. The experimental results show that the proposed 3D information hiding method based on projection sampling is a high-capacity hiding technique with the embedding capacity of up to 5 bits per vertex (bpv). The method exhibits excellent imperceptibility, with a minimum PSNR of 51 dB at maximum embedding capacity. It can completely resist to reordering attacks. The correlation coefficients are nearly 1 for extracting watermarks from individual or simultaneous coordinate translations and scale changes along the X and Y axes. It can resist cropping attacks with cropping ratios less than 15% (correlation coefficient greater than 0.75), and exhibits a certain level of resilience to additive noise.