数字图像盲取证对样本合成修复应用的篡改区域检测算法  

A Blind Forensic Algorithm for Detecting Doctored Image Region by Application of Exemplar-based Image Completion

作　　者：吴琼[1] 孙韶杰[1] 朱为[1] 李国辉[1] 涂丹[1] 何朝盛 

机构地区：[1]国防科技大学信息系统与管理学院,长沙410073 [2]南昌陆军学院,南昌330103

出　　处：《自动化学报》2009年第3期239-243,共5页Acta Automatica Sinica

摘　　要：提出了一种图像盲取证算法,用于检测利用样本合成修复技术制作的伪造图像.该算法采用零连通特征来描述修复技术导致的图像块之间异常的相似性,然后构建升半梯形隶属函数将该相似性特征转换成块属于篡改块的模糊隶属度,通过截集划分并结合高隶属度块的位置信息,进行伪造图像的检测和篡改区域的定位.实验结果表明该算法能够有效区分自然图像和修复伪造图像,并可进一步定位图像的篡改区域.This paper presents a blind image forensic algorithm for detecting forged images created by exemplar-based image completion technique. First, the zero-connectivity feature is used to describe the abnormal similarity of image block pairs caused by completion, and then the semi-trapezoid membership function is built up to translate the similarity characteristics of blocks into the fuzzy membership of tampered block. The tampered regions of forged image are localized by cutting the fuzzy set combining the location information of high membership blocks. The experimental results show that our algorithm can effectively distinguish natural images from inpainted forged images, and further localize the tampered regions.

关 键 词：图像盲取证 图像修复 零连通 模糊隶属度 样本合成 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]