基于图像能量的稳健图像哈希算法  

Robust image hashing algorithm based on image energy

作　　者：袁晓冉 赵琰 Yuan Xiaoran;Zhao Yan(College of Electronics&Information Engineering,Shanghai University of Electric Power,Shanghai 200120,China;Guangxi Key Laboratory of Multi-Source Information Mining&Security,Guangxi Normal University,Guilin Guangxi 541004,China)

机构地区：[1]上海电力大学电子与信息工程学院,上海200120 [2]广西师范大学广西多源信息挖掘与安全重点实验室,广西桂林541004

出　　处：《计算机应用研究》2021年第6期1900-1906,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(61802250);广西多源信息挖掘与安全重点实验室开放基金资助项目(MIMS18-04)。

摘　　要：为了提高哈希算法的分类性能和运行效率,提出一种基于梯度变化特征和能量特征的图像哈希算法。首先,对输入图像进行预处理操作形成二次图像,利用Sobel算子对二次图像的红色通道、绿色通道、蓝色通道图像进行x轴和y轴的梯度值计算,将各分量图像的梯度值进行相加得到最终的梯度图像;然后将梯度图像幅值的多方向变化信息作为图像的梯度特征,所有图像子块的能量值作为图像的能量特征;最后将图像的梯度特征与能量特征联合起来并置乱得到最终的哈希序列。实验结果表明:所提算法的区别性和鲁棒性可以达到较好的权衡;与最新的以及较好的哈希算法相比,该算法具有最好的ROC曲线和最短的运行时间,平均运行时间为0.0242 s,并且在拷贝检测的对比实验中,所提算法的查全率—查准率曲线最好。In order to improve the classification performance and operation efficiency of the hash algorithm,this paper proposed an image hash algorithm based on gradient change feature and energy features.Firstly,the algorithm preprocessed the input image to obtain a secondary image,and used the Sobel operator to calculate the x-axis and y-axis gradient values of the red channel,green channel,and blue channel images of the secondary image.It added the gradient values of the images to obtain the final gradient image.Then it used the multi-directional change information of the gradient image amplitude as the gradient feature,and used the energy values of all image subblocks as the energy features.Finally,it combined and scrambled the gradient feature and energy features of the image to generate the final hash sequence.The experimental results show that:the discrimination and robustness of the proposed algorithm can achieve a good trade-off;compared with the latest and excellent hash algorithms,this algorithm has best ROC curve and the shortest average running time 0.0242 s,and in the comparison experiment of copy detection,the R-P curve of the proposed algorithm is the best.

关 键 词：图像哈希 梯度特征 能量特征 拷贝检测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]