Robust forensics for image regional duplication and forgery based on DWT and Zernike moment

WANG Jun-wen; LIU Guang-jie; ZHANG-Zhan; DAI Yue-wei; WANG Zhi-quan

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Robust forensics for image regional duplication and forgery based on DWT and Zernike moment

Article | 更新时间：2020-08-12

- Robust forensics for image regional duplication and forgery based on DWT and Zernike moment
- Optics and Precision Engineering Vol. 17, Issue 7, Pages: 1686-1693(2009)
- 作者机构：
  
  南京理工大学自动化学院,江苏南京,210094
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Received：26 August 2008，
  
  Revised：08 October 2008，
  
  Published Online：25 July 2009，
  
  Published：25 July 2009
- 稿件说明：
移动端阅览
王俊文, 刘光杰, 张湛, 戴跃伟, 王执铨. 基于小波变换和Zernike矩的图像区域复制篡改鲁棒取证[J]. 光学精密工程, 2009,17(7): 1686-1693

WANG Jun-wen, LIU Guang-jie, ZHANG-Zhan, DAI Yue-wei, WANG Zhi-quan. Robust forensics for image regional duplication and forgery based on DWT and Zernike moment[J]. Editorial Office of Optics and Precision Engineering, 2009,17(7): 1686-1693
王俊文, 刘光杰, 张湛, 戴跃伟, 王执铨. 基于小波变换和Zernike矩的图像区域复制篡改鲁棒取证[J]. 光学精密工程, 2009,17(7): 1686-1693 DOI：

WANG Jun-wen, LIU Guang-jie, ZHANG-Zhan, DAI Yue-wei, WANG Zhi-quan. Robust forensics for image regional duplication and forgery based on DWT and Zernike moment[J]. Editorial Office of Optics and Precision Engineering, 2009,17(7): 1686-1693 DOI：

摘要

针对现有的图像区域复制篡改检测算法其后处理的鲁棒性较差

且时间复杂度高的问题

提出了一种有效的检测与定位篡改区域算法。该算法通过对图像进行小波分解

将低频图像进行块分解

提取每块的Zernike矩特征

并将特征向量排序;然后

为每个特征向量搜索阈值符合的相似特征向量;最后

利用区域面积阈值去除错误的相似块对

并结合数学形态学定位篡改区域。实验结果表明

该算法不仅能有效地对抗常规的后处理操作

而且只在1/4图像上搜索块空间

提高了运算效率。本方法可用于面向图像内容的真实性鲁棒取证。

Abstract

Most of the existing detection algorithms for testing the region duplication and forgery are not robust in the post region duplication image process

and have high time complexities. In this paper

an efficient and robust algorithm is presented for detecting and localizing this type of malicious forgery.After reducing the image dimension by Discrete Wavelet Transform(DWT)

the Zernike moment is applied to the fixed sized overlapping blocks of a low-frequency image in the wavelet sub-band

and the eigenvectors are lexicographically sorted. Then

similar eigenvectors are matched by a certain threshold. Finally

the area threshold is proposed to remove the wrong similar blocks

and the mathematical morphology operations are performed to localize the forgery part. Experimental results show that proposed method is robust and not only can successfully detect this type of forgery for images subjected to post region duplication processing in various forms

but also can search block spaces in only the 1/4 image

which improves the calculation efficiency of algorithm. The method suits to the robust forensics for image contents.

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Keywords

references

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