一种基于逆序广义2近邻的图像多重复制粘贴篡改检测算法  

Image Multiple Copy-move Forgery Detection Algorithm Based on Reversed-generalized 2 Nearest-neighbor

作　　者：李岩[1] 刘念[2] 张斌[3] 袁开国[1] 杨义先[1] 

机构地区：[1]北京邮电大学信息安全中心,北京100876 [2]北京电子科技学院,北京100070 [3]中国信息安全认证中心,北京100020

出　　处：《电子与信息学报》2015年第7期1667-1673,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61170271;61121061);新闻出版署项目(GXTC-CZ-1015004/15-1);中央高校基本科研业务费专项资金(BUPT2012RC0217)资助课题

摘　　要：为了解决数字图像多重复制粘贴篡改检测问题,克服广义2近邻(g2NN)算法对匹配特征点漏检的缺点,该文提出逆序广义2近邻(Rg2NN)算法。在计算匹配特征点时,该算法采用逆序方式计算特征点之间的匹配关系,可以更加准确地计算出所有与待检测特征点相匹配的特征点。实验证明,Rg2NN算法比g2NN算法计算出来的匹配特征点更加准确,提高了g2NN算法对多重复制粘贴篡改图像的检测能力,当图像中的一块区域被复制后在多处粘贴,或多块区域被复制粘贴时可以准确计算出复制粘贴区域。For the consideration of the multiple copy-move forgery detection of digital images, and to avoid mmsmg the matching feature points when generalized 2 Nearest-Neighbor （g2NN） algorithm is applied, Reversed generalized 2 Nearest-Neighbor （Rg2NN） algorithm is proposed. Reverse order is used in feature points matching, so that all feature points that match with the detected point can be calculated accurately. The experiment results show that the matching feature points calculated by Rg2NN are more accurate than by g2NN, and the ability of g2NN in detecting multiple copy-move forgery is improved. When one patch in the image is copied and pasted multiple times or two or more patches are copied and pasted, the copy-move map can be localized precisely by the Rg2NN algorithm.

关 键 词：图像处理 图像取证 复制粘贴 特征点 

分 类 号：TN911.73[电子电信—通信与信息系统]