摘要
现有的复制–粘贴盲鉴别算法大多忽略图像彩色信息,导致对隐蔽性篡改方式的检测率较低,基于此,本文提出一种基于彩色局部二值模式(Color local binary patterns,Co LBP)的隐蔽性复制–粘贴盲鉴别算法.算法首先对彩色图像进行预处理,即建立彩色LBP纹理图像,从而实现彩色信息与LBP纹理特征的融合;其次重叠分块并提取灰度共生矩阵(Gray level co-occurrence matrix,GLCM)特征;最后,提出改进的kd树和超平面划分标记split搜索方法,快速匹配图像块,并应用形态学操作去除误匹配,精确定位复制–粘贴区域.实验结果表明,本算法对隐蔽性复制–粘贴篡改定位准确,并对模糊、噪声、JPEG重压缩后处理操作有很好的鲁棒性.
Since negligence of color information in detecting copy-move forgeries leads to low accuracy in detection of in covert tampering, a novel method using color local binary patterns(CoLBP) is proposed. It involves the following three steps: first, establish color LBP texture image, which is a preprocessing of image and a combination of color information and LBP texture; second, divide into overlapping blocks and extract gray level co-occurrence matrix(GLCM)features; finally, match image blocks by the improved kd tree and split partition, remove the false matched blocks using morphological operation and then detect the resulting copy-move regions. Experimental results show that our algorithm is effective for covert tampering, and exhibits high robustness even when an image is distorted by blur, noise and JPEG recompression.
出处
《自动化学报》
EI
CSCD
北大核心
2017年第3期390-397,共8页
Acta Automatica Sinica
基金
国家青年科学基金(61305046
61602203)
吉林省自然科学基金(20140101193JC
20150101055JC)资助~~
关键词
图像盲鉴别
复制–粘贴篡改
彩色局部二值模式
灰度共生矩阵
KD树
Image blind identification
copy-move forgery
color local binary patterns(CoLBP)
gray level co-occurrence matrix(GLCM)
kd tree