基于自适应直方图修改的网格可逆信息隐藏

可逆信息隐藏是一种特殊的信息隐藏技术， 在医学、军事和法律等领域具有重要的应用价值.本文提出一种基于自适应直方图修改的网格可逆信息隐藏算法. 首先， 利用模型形状的局部相似性， 预测顶点位置以获得预测误差序列， 构造陡峭的预测误差直方图. 然后， 根据直方图的分布特点， 直接使用嵌入区域内两组指定的预测误差来嵌入秘密信息，减少了辅助信息的传输. 最后， 为减少模型失真， 根据载荷大小自适应地选取合适的嵌入区域， 有效避免对预测误差过多移动. 实验结果表明， 本文提出的算法在小容量嵌入时能保持较高的视觉质量， 适用于高保真的网格可逆信息隐藏.

Reversible Data Hiding Algorithm Based on Adaptive Histogram Modification for 3D Mesh Models

Reversible data hiding， as a special information hiding technology， is very useful in many fields， such as medicine， military and law. This paper proposes a reversible data hiding algorithm based on adaptive histogram modification for 3D mesh models. At first， the local similarity of model shapes is used to predict vertex positions in order to obtain the prediction error sequence with a steep histogram. Then， according to the distribution characteristics of the prediction error histogram， two groups of prediction errors are specified in embedding region for data embedding，which reduce the auxiliary date transfer. In addition， to reduce the model distortion， proper embedding regions are selected based on the payload size to avoid moving more prediction errors. The experimental results demonstrate that the proposed algorithm maintains high visual quality after data embedding and is applicable to low-capacity reversible data hiding.