Image splicing detection based on high frequency wavelet Markov features

doi:10.11772/j.issn.1001-9081.2014.05.1477

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (5): 1477-1481.DOI: 10.11772/j.issn.1001-9081.2014.05.1477

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Image splicing detection based on high frequency wavelet Markov features

YUAN Quanqiao¹,SU Bo¹,ZHAO Xudong²,LI Shenghong²

1. School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;
2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2013-10-17 Revised:2014-01-09 Online:2014-05-30 Published:2014-05-01
Contact: SU Bo
Supported by:
National Natural Science Foundation

基于高频小波子带马尔可夫特征的图像拼接检测

袁全桥¹,苏波¹,赵旭东²,李生红²

1. 上海交通大学信息安全工程学院，上海 200240
2. 上海交通大学电子信息与电气工程学院，上海 200240

通讯作者: 苏波
作者简介:袁全桥（1988-），男，河南南阳人，硕士研究生，主要研究方向：数字图像防伪；苏波（1972-），男，上海人，副教授，博士研究生，主要研究方向：信息内容安全、安全管理；赵旭东（1981-），男，江苏徐州人，博士研究生，主要研究方向：数字图像取证、图像处理；李生红（1971-），男，上海人，教授，博士，主要研究方向：信息内容、信号处理、模式识别。
基金资助:
国家自然科学基金资助项目;国家重点研究发展“973”计划;“十二五”国家科技支撑计划

Abstract

Abstract:

Splicing is the most universal image tampering operation, detection of which is effective for identifying image tamper. A blind splicing detection method was proposed. The method firstly analyzed the effects of different sub-bands on image splicing detection according to features of wavelet transform. High frequency sub-band was verified to be more appropriate for splicing detection both from theory analysis and experiment results. Secondly, the method conducted difference operation, rounded and made threshold to the coefficients as discrete Markov states, and calculated the state transition probabilities as splicing features. Finally, Support Vector Machine (SVM) was used as classifier, and the features were tested on Columbia image splicing detection evaluation datasets. The experimental results show that the proposed method performs better compared with other features and achieves a detection accuracy rate of 94.6% on the color dataset specially.

摘要：

拼接是图像篡改过程中最普遍使用的操作，通过检测拼接可以有效鉴别图像是否经过人为修改。针对拼接操作提出了一种盲检测方法：首先对图像进行小波变换，在比较分析不同小波子带对图像拼接检测的作用后，选取高频子带作为图像变换域信息；接着对小波子带进行差分操作，并将系数取整阈值化后作为马尔可夫状态；最后计算状态间的转移概率作为拼接特征，利用支持向量机（SVM）进行分类。在哥伦比亚图像拼接评测彩色库和灰度库上分别进行实验，证实了选取小波高频子带提取拼接特征的有效性。通过与其他特征提取方法对比，所提出特征在两个评测库上都表现出了更好的检测效果，尤其在彩色评测库上取得了94.6%的识别率。

CLC Number:

TP391.4

YUAN Quanqiao SU Bo ZHAO Xudong LI Shenghong. Image splicing detection based on high frequency wavelet Markov features[J]. Journal of Computer Applications, 2014, 34(5): 1477-1481.

袁全桥苏波赵旭东李生红. 基于高频小波子带马尔可夫特征的图像拼接检测[J]. 计算机应用, 2014, 34(5): 1477-1481.

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Image splicing detection based on high frequency wavelet Markov features

基于高频小波子带马尔可夫特征的图像拼接检测

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