摘要
针对图像篡改时可能会经历重采样操作,而重采样过程中的插值步骤会对重采样图像像素引入一定的线性相关性的问题,提出一种重采样检测算法.采用奇异值分解度量像素间的线性相关性,针对纹理复杂程度不同的子像素块分析插值处理对其线性相关性的影响;以零奇异值个数和奇异值均值作为分类特征,结合SVM进行重采样检测.实验结果表明,该算法能够实现对重采样图像和原始图像的准确分类.
When images are tampered,they may undergo resampling manipulation.A resampling detection algorithm is proposed,which is designed to detect the changes brought into the linear dependencies of the image pixels introduced by the interpolation process of resampling.The specific statistical changes with different texture complexity are analyzed by singular value decomposition,the number and mean value of small singular values are used as distinguishing features,and SVM is used to classify.The performance of resampling detection shown in experimental results indicates the validity of the algorithm.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第9期1606-1612,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60473022)
关键词
图像盲取证
篡改检测
重采样检测
奇异值分解
纹理复杂度
blind image forensics
tempering detection
resampling detection
singular value decomposition
texture complexity
