基于非负矩阵分解的图像复制粘贴伪造检测

赵中武; 焦丽鑫

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基于非负矩阵分解的图像复制粘贴伪造检测

更新时间：2026-09-04

- 基于非负矩阵分解的图像复制粘贴伪造检测
- Copy-paste Forgery Detection Based on Non-negative Matrix Factorization
- 微电子学与计算机 2016年33卷第6期页码：23-26
- 作者机构：
  
  南京工业大学机构计算机科学与技术学院,江苏,南京,211816
- 作者简介：
- 基金信息：
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- 纸质出版：2016
- 稿件说明：
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赵中武, 焦丽鑫. 基于非负矩阵分解的图像复制粘贴伪造检测[J]. 微电子学与计算机, 2016, 33(6): 23-26.

ZHAO Zhong-wu, JIAO Li-xin. Copy-paste Forgery Detection Based on Non-negative Matrix Factorization[J]. 2016, 33(6): 23-26.
赵中武, 焦丽鑫. 基于非负矩阵分解的图像复制粘贴伪造检测[J]. 微电子学与计算机, 2016, 33(6): 23-26. DOI：

ZHAO Zhong-wu, JIAO Li-xin. Copy-paste Forgery Detection Based on Non-negative Matrix Factorization[J]. 2016, 33(6): 23-26. DOI：

摘要

复制粘贴伪造是图像篡改的一种重要手段

由此提出一种利用非负矩阵分解的检测算法来识别图像中存在的复制粘贴伪造.该算法选取重叠分块后的图像子块作为基本比较单元

对图像块进行离散小波变换

提取低频近似分量

利用非负矩阵分解对每个图像子块提取到的低频近似分量进行二次特征提取

得到系数矩阵

并进一步对其进行二值量化

最后将量化后的系数矩阵作为图像块的特征表述

利用Jaccard相似度衡量图像块间的相似度进行篡改检测

得到复制粘贴伪造区域.实验结果表明

所提算法在减少运算量、降低复杂度的基础上

可以高效地检测出图像中存在的复制粘贴伪造区域

同时具有鲁棒性.

Abstract

Copy-paste forgery is an important means of image tampering

an efficient and passive approach based on Non-negative matrix factorization is presented to detect the copy-paste forgery in the digital image. Firstly

image is segmented into overlapping blocks as the basic comparing unit

then DWT is applied to each sub-block and the low-frequency component is extracted. Non-negative matrix factorization of the low-frequency component is used to yield a reduced coefficient matrix which will be quantized subsequently as the features of sub-block. At last the detection is measured by the Jaccard similarity between each two sub-blocks. The experimental results show that the proposed algorithm is efficient and robust to the forgery detection of copy-paste image with less amount of computation and complexity.

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references

Li G, Wu Q, Tu D, et al. A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD[C]//Multimedia and Expo, 2007 IEEE International Conference on. China, Beijing, 2007: 1750-1753.

Li W, Yu N. Rotation robust detection of copy-move forgery[C]//Proc. IEEE International Conference on Image Processing ICIP'10. China, Hongkong, 2010: 2113-2116.

Popescu A C, Farid H. Exposing digital forgeries by detecting duplicated image regions[R]. Dartmouth College, Computer Science, TR2004-515, 2004.

Mahdian B, Saic S. A bibliography on blind methods for identifying image forgery[J]. Signal Processing: Image Communication, 2010, 25(6): 389-399. DOI: 389

Fridrich J, Soukal D, Lukas J. Detecting of copy-move forgery in digital images[C]//Proc. Digital Forensic Research Workshop. Cleveland, OH, 2003.

张小祥, 周治平. 小波低频子带提取特征的图像复制篡改检测[J]. 计算机工程与应用, 2011, 47(10): 161-163. DOI: 161

叶娇娇, 陈明志. 基于小波矩的图像复制粘贴篡改检测[J]. 计算机系统应用, 2013, 22(12): 108-112. DOI: 108

Mahdian B, Saic S. Detection of copy-move forgery using a method based on blur moment invariants[J]. Forensic Science International, 2007, 171(2/3): 180-189. DOI: 180

岳芹. 基于DWT域数字水印的遥感图像机密信息隐藏[J]. 计算机与现代化, 2009, 24(8): 150-151. DOI: 150

Lee D D, Seung H S. Learning the parts of objects with non-negative matrix factorization[J]. Nature, 1999, 130(401): 788-791. DOI: 788

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