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论文摘要

图像内部Move-Copy篡改盲取证算法研究

Research of Internal Image Move-Copy Tampering Forensics Algorithm

作者:李若晨(四川大学计算机学院);琚生根(四川大学计算机学院);周刚(四川大学计算机学院);邵寿平(四川大学计算机学院)

Author:LI Ruo-Chen(College of Computer Science, Sichuan University);JU Shen-Gen(College of Computer Science, Sichuan University);ZHOU Gang(College of Computer Science, Sichuan University);SHAO Shou-Ping(College of Computer Science, Sichuan University)

收稿日期:2015-06-08          年卷(期)页码:2016,53(1):67-72

期刊名称:四川大学学报: 自然科学版

Journal Name:Journal of Sichuan University (Natural Science Edition)

关键字:Move-Copy图像篡改; 颜色不变; Surf描述; 噪声敏感系数; 肯德尔系数

Key words:Move-Copy Image tampering; Color invariant; Surf descriptor; Noise-sensitive factor; Kendall coefficient

基金项目:国家自然科学基金(81373239,61332006)

中文摘要

针对一般Move-Copy图像篡改取证算法低鲁棒性特点,提出新算法。首先利用颜色不变量检测特征点位置,提高特点的数量和取证结果的召回率;其次用RGB颜色通道扩充Surf描述子向量维数,提高特征向量的健壮性和鲁棒性;然后定义噪声敏感系数判断图像噪声点并对之进行预处理;接着利用序贯相似性检测算法对特征点进行配准以提高配准速度;最后利用肯德尔系数和四条假设对取证结果进行约束,得到最后结果。实验结果表明,本文算法取证准确率较高,鲁棒性强,具有较强的取证说服力。

英文摘要

According to the low robustness characteristics of image tampering with evidence of general move-copy algorithm, this paper proposes a new algorithm. Firstly, it uses the color invariant feature to detect feature points, which improves recall forensic results. Secondly, it uses the RGB color channel to expansion Surf descriptor, which increases the robustness of feature vectors. Then, it defines noise sensitivity coefficients to identify and deal with the image noise points and use sequential similarity detection algorithm to improve feature points registration. Finally, it uses Kendall coefficient and the four hypothesis to constrain the forensic results and get the final result. Experimental results show that the new algorithm reflects higher accuracy and strong robustness and it has strong ability of forensics.

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