基于超像素形状特征的图像复制粘贴篡改检测算法  

Image copy-move forgery detection algorithm based on superpixel shape features

作　　者：魏伟一 王立召 王婉茹 赵毅凡 WEI Wei-yi;WANG Li-zhao;WANG Wan-ru;ZHAO Yi-fan(School of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China)

机构地区：[1]西北师范大学计算机科学与工程学院,甘肃兰州730070

出　　处：《计算机工程与科学》2021年第2期312-321,共10页Computer Engineering & Science

基　　金：甘肃省科技计划-自然科学基金(20JR5RA518)。

摘　　要：针对传统图像复制粘贴篡改检测方法中划分子块的数目过大导致算法时间复杂度过高且抵抗几何变换能力较弱的问题,提出一种基于超像素形状特征的图像复制粘贴篡改检测算法。首先提出基于小波对比度自适应划分超像素的方法分割图像并提取稳定的特征点;然后提出新颖的形状编码方式提取超像素形状特征,并与特征点融合,估计可疑伪造区域;最后对可疑伪造区域进行二次超像素分割和匹配,精确定位篡改区域。实验结果表明,提出的算法具有抵抗几何变换、噪声、模糊和JPEG压缩的能力。Aiming at the problem that the excessively large number of divided sub-blocks in the traditional image copy-move forgery detection methods cause high algorithm time complexity and weak ability to resist geometric transformation,an image copy-move forgery detection algorithm based on superpixel shape features is proposed.Firstly,an adaptive division method of superpixels based on wavelet contrast is proposed to segment the image,and the stable feature points are extracted.Secondly,a novel shape coding scheme is proposed to extract superpixel shape features,which are merged with the feature points to estimate the suspected forged regions.Finally,the suspicious forged regions are segmented into superpixels again and matched to accurately locate the tampered areas.Experimental results show that the proposed method has the ability to resist geometric transformation,noise,blur and JPEG compression.

关 键 词：复制粘贴篡改检测 形状特征 超像素 特征点 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]