期刊文献+

离散小波变换耦合静电场理论的图像快速伪造检测算法 被引量:3

Image Fast Forgery Detection Algorithm Based on Discrete Wavelet Transform Coupled Electrostatic Field Theory
下载PDF
导出
摘要 为了解决当前图像伪造检测算法主要是在图像空域中定位伪造区域,难以降低图像维数,使其复杂度大;且不能有效检测几何变换篡改形式的伪造区域,导致其鲁棒性不佳的不足,提出了离散小波变换耦合静电场理论的图像伪造检测算法;首先,引入离散小波变换,提取伪造图像的低频子带,降低图像空间;再基于静电场理论,将提取子带映射到虚拟电场中,提取鲁棒性较强的特征,利用Radix排序算法对特征完成重组,形成特征矩阵;最后,定义相同仿射变换,并用其处理排序矩阵,完成伪造区域检测;实验测试结果显示:与当前的移动复制伪造检测技术相比,所提算法具有更高的定位效率与检测精度;同时拥有较强的鲁棒性,有效抗击几何变换篡改;该算法能够高效精确检测几何变换伪造形式的图像内容。 In order to solve the problems such as big complexity induced by difficultly reducing the image dimension mainly in the space domain for locating forged regions,and the poor robustness caused by difficultly detecting geometric transform tamper form the forged areas in current image forgery detection algorithm,the image fast forgery detection algorithm is proposed based on discrete wavelet transform coupled electrostatic field theory.Firstly,the low frequency subbands of forged images were extracted by introducing the discrete wavelet transform for reducing the image space.Then the strong robustness feature was extracted based on electrostatic field theory for mapping the extracted subbands to virtual electric field,as well as these features were ordered by Raster scanning to form feature matrix.Finally,the affine transformation was used to deal with the matrix for finishing the forgery detection.Test results show that:this algorithm had higher location efficiency and detection precision,as well as strong robustness to effectively against geometric transform tampering compared with the current move-copy forgery detection technology.This algorithm can efficiently and accurately detect the image content of forgery image with geometric transformation.
出处 《计算机测量与控制》 2016年第3期44-47,共4页 Computer Measurement &Control
基金 四川省教育厅理工科重点项目(14ZA0339)
关键词 图像伪造检测 离散小波变换 静电场 Radix排序 仿射变换 image forgery detection discrete wavelet transform electrostatic field raster scan affine transformation
  • 相关文献

参考文献13

  • 1Shin Y D. Fast detection of Duplicated Forgery Image using Sub-- sampling [J]. Journal of Convergence Information Technology, 2015, 10 (2):17-25.
  • 2李香花,赵于前,廖苗,F.Y.Shih,Y.Q.Shi.Passive detection of copy-paste forgery between JPEG images[J].Journal of Central South University,2012,19(10):2839-2851. 被引量:5
  • 3Ansari M, Ghrera S P, Tyagi V. Pixel--Based Image Forgery De- tection: A Review [J]. IETE Journal of Education, 2014, 55 (1) : 40 - 46.
  • 4Hashmi M F, Anand V, Keskar A G. Copy--move Image Forgery Detection Using an Efficient and Robust Method Combining Un-- decimated Wavelet Transform and Scale Invariant Feature Trans- form [J]. AASRIProcedia, 2014, 12 (9): 84-91.
  • 5Liu B, Pun C M, Yuan X C. Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies [J]. The Scientific World Journal, 2014, 33 (12): 1257-1268.
  • 6Parul M, Nishchol M, Sanjeev S. Region duplication forgery detec- tion technique based on SURF and HAC [J]. Scientific World Jour- nal, 2014, 7 (11): 256-267.
  • 7Bouda B, Lh. Masmoudi, D. Aboutajdine. Cubical voxels and vir- tual electric field model for edge detection in color images [J]. Sig- nal Processing, 2011, 88 (4): 905-915.
  • 8Lin H M, Xu Z L, Tang H Z. Image Approximations to Electro- static Potentials in Layered Electrolytes/Dielectrics and an Ion- Channel Model [J]. Journal of Scientific Computing, 2012, 53 (2): 249 - 267.
  • 9胡亦,王琳娜,朱恭生,陈钟.锯齿空间填充曲线耦合压缩感知的彩图灰度化实时加密算法[J].激光杂志,2015,36(2):12-18. 被引量:11
  • 10Ye J, Chen J X, Chen X Q. Modeling and Rendering of Real-- time Large--scale Granular Flow Scene on GPU [J]. Procedia Envi- ronmental Sciences, 2011, 10 (2): 1035 -1045.

二级参考文献72

  • 1黄小为,吴传生,朱华平.求解不适定问题的TSVD正则化方法[J].武汉理工大学学报,2005,27(2):90-92. 被引量:15
  • 2梁欣,谭月辉,张俊萍,刘凯.MATLAB在图像数字水印技术研究中的运用[J].科学技术与工程,2006,6(15):2264-2267. 被引量:6
  • 3朱朝杰,王仁礼,董广军.MATLAB环境下遥感影像配准与融合技术研究[J].测绘工程,2006,15(6):57-59. 被引量:6
  • 4MAHDIAN B, SAIC S. A bibliography on blind methods fbr identifying image forgery [J]. Signal Processing: Image Communication, 2010, 25(6): 389 399.
  • 5CHAMLAW1 R, KHAN A. Digital image authentication and recovery: Employing integer transform based information embedding and extraction [J]. information Sciences, 2010, 180(24): 4909-4928.
  • 6MAHDIAN B, SAIC S. Using noise inconsistencies for blind image forensics [J]. Image and Vision Computing, 2009, 27(10): 1497-1503.
  • 7FARID H. A survey of image forgery detection [J]. IEEE Signal Processing Magazine, 2009, 26(2): 16-15.
  • 8CAO Hong, KOT A C. Detection of tampering inconsistencies on mobile photos [C]// 9th International Workshop on Digital Water- marking, Seoul. Korea, 2010: 1-11.
  • 9LI Wei-hai, YUAN Yuan, YU Neng-hai. Passive detection of doctored JPEG image via block artifact grid extraction [J]. Signal Processing, 2009, 89(9): 1821-1829.
  • 10LUO Wei-qi, QU Zhen-hua, HUANG Ji-wu, QIU Guo-ping. A novel method for detecting cropped and recompressed image block [C]// IEEE International Conference on Acoustics, Speech and Signal Processing. Honolulu, Hawaii, USA, 2007: II-217- II-220.

共引文献23

同被引文献31

引证文献3

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部