计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 135-138.

• 模式识别与图像处理 • 上一篇    下一篇

基于异常预测特征量的拼接图像检测方法

侯俊,程燕   

  1. 上海理工大学光电信息与计算机工程学院 上海400047;华东政法大学计算机科学与技术系 上海200610
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受教育部人文社科项目(11YJCZH175),华东政法大学校级科研项目资助

Detection of Spliced Photographic Based on Abnormal Prediction Features

HOU Jun and CHENG Yan   

  • Online:2018-11-14 Published:2018-11-14

摘要: 提出了一种对由多张数字图像合成的伪造图像进行鉴定的方法。算法首先采用基于树图的归一化分割方法将图像进行划分,使得分割区域内部紧致度达到最大而同时分割形成的区域间分裂性最小,得到符合视觉感受的区域分割结果;接着采用八邻点的最小二乘法预测图像各像素点值,分别计算域内、域间预测异常的统计特征,同时考虑到预测异常与图像本身的纹理有关系,对反映纹理特征的共生矩阵计算特征统计量,将所有特征送入经过训练的支持矢量机进行图像鉴别。实验结果表明所提出的特征能有效鉴别合成图像。

关键词: 图像伪造,合成图像,归一化割,共生矩阵,支持矢量机 中图法分类号TP309.7文献标识码A

Abstract: The paper proposed an algorithm to expose spliced photographic merging two or more parts from different photos into one composite.The proposal algorithm firstly segments photo into several parts under perceptual grouping criterion,minimizing the disassociation between parts and maximizing combination within part with normalized cut algorithm,then predicts each pixel’s value according to its eight neighbors by minimal least square methods,conducts statistical features of inharmonic points.Since these features are influenced by texture characteristics,features of co-occurrence matrix,which display the image’s texture,are also calculated.Finally,all features are feeded to a support vector machine (SVM) classifier.The test experiments show that the proposal method is effective in exposing splicing image.

Key words: Image forgery,Spliced photographic,Normalized cut,Co-occurrence matrix,Support vector machine

[1] Nguyen H C.Detection of copy-move forgery in digital images using radon transformation and phase correlation[C]∥Procee-dings of Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.2012:134-137
[2] Popescu A C,Farid H.Exposing digital forgeries by detecting duplicated image regions.http://www.cs.dartmouth.edu /farid/downloads/publications/tr04.pdf,department of compu-ter.science,dartmouth college,2012
[3] Kee E,Farid H.A perceptual metric for photo retouching[J].Proceedings of the national academy of sciences,2011,108(50):19907-19912
[4] O’Brien J,Farid H.Exposing photo manipulation with inconsistent reflections[J].ACM transactions on graphics,2012,31(1):1-11
[5] Kee E,Johnson M K,Farid H.Digital image authentication fromjpeg heads[J].IEEE transactions on information forensics and security,2011,6(3):1066-1075
[6] Zheng Qian-ru,Sun Wei,Lu Wei.Digital spliced image forensics based on edge blur measurement[C]∥Proceedings of IEEE International Conference on Information Theory and Information Security.Dec.2010:399-402
[7] Gou Hong-mei,Swaminathan A,Wu Min.Noise features for image tampering detection and steganalysis[C]∥Proceeding of IEEE Conference on Image Processing.2007,6:97-100
[8] Shi Jian-bo,Malik J.Normalized cuts and image segmentation[J].IEEE transactions on pattern analysis and machine intelligence,2000,22(8):888-905
[9] Hsu Yu-feng,Chang Shih-fu.Camera response functions for image forensics:an automatic algorithm for splicing detection[J].IEEE transactions on information forensics and security,2010,5(4):816-825
[10] Chen Ying,Wang Yu-ping.Exposing digital forgeries by detecting traces of smoothing[C]∥Proceeding of 9th International Conference for Young Computer Scientists.2008:1440-1445
[11] Libsvm.http://www.csie.ntu.edu.tw/~cjlin/

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