基于Tchebichef矩与颜色矢量角度的鲁棒图像哈希算法

Robust image Hashing algorithm based on Tchebichef moments and Color Vector Angle

摘要:

为了改善哈希算法对旋转等内容修改的鲁棒性，设计了径向Tchebichef矩耦合颜色矢量角度的鲁棒图像哈希算法。引入2D离散小波变换(DWT)，对图像的颜色矢量角度实施分解，获取对应的4个子带，将其低频系数作为结构特征。采用径向Tchebichef矩计算预处理图像的Tchebichef矩，提取全局特征。通过组合这2种特征，以形成中间哈希序列。设计加密函数，对中间哈希完成加密，得到目标哈希序列。计算初始目标与待识别图像的哈希序列之间的l₂范数距离，并将其与预设阈值作比较，完成图像内容的真伪判别。测试数据表明：相对于已有的哈希算法而言，所提算法具备更高的鲁棒性，可以对旋转、颜色与缩放等内容修改做出准确识别。

Abstract:

In order to improve the robustness of the Hashing algorithm for the content modification such as rotation, a robust image Hashing algorithm based on radial Tchebichef moment and Color Vector Angle(CVA) is designed in this paper. The 2D Discrete Wavelet Transform(DWT) is introduced to decompose the color vector angle of image for obtaining four sub-bands, and the low frequency coefficients are taken as structural features. The Tchebichef moments of pre-processing image are calculated based on radial Tchebichef moments to extract global features. And an intermediate Hash sequence is got by combining the two features. The encryption function is designed to encrypt the intermediate Hash for obtaining the target Hash sequence. Finally, the l₂ norm distance between the initial target and the Hash sequence of the recognized image is calculated, and the authenticity discrimination of the image content is finished by comparing it with the preset threshold. The test data shows that this proposed Hashing algorithm is more robust than the existing Hashing algorithm, which can accurately identify the modifications of rotation, color and scaling.