Exposing image forgery by detecting traces of feather operation

Powerful digital image editing tools make it very easy to produce a perfect image forgery. The feather operation is necessary when tampering an image by copy-paste operation because it can help the boundary of pasted object to blend smoothly and unobtrusively with its surroundings. We propose a blind technique capable of detecting traces of feather operation to expose image forgeries. We model the feather operation, and the pixels of feather region will present similarity in their gradient phase angle and feather radius. An effectual scheme is designed to estimate each feather region pixel's gradient phase angle and feather radius, and the pixel's similarity to its neighbor pixels is defined and used to distinguish the feathered pixels from un-feathered pixels. The degree of image credibility is defined, and it is more acceptable to evaluate the reality of one image than just using a decision of YES or NO. Results of experiments on several forgeries demonstrate the effectiveness of the technique. A blind technique of detecting traces of feather operation image forgeries.Modeling influence of feather operation by gradient phase angle and radius.An approach to expose image forgeries region by traces of feather operation.The degree of credibility is defined to evaluate the reality of one image.

[1]  Korris Fu-Lai Chung,et al.  Revealing digital fakery using multiresolution decomposition and higher order statistics , 2011, Eng. Appl. Artif. Intell..

[2]  Wei Sun,et al.  Improved DCT-based detection of copy-move forgery in images. , 2011, Forensic science international.

[3]  Hany Farid,et al.  Exposing Digital Forgeries From JPEG Ghosts , 2009, IEEE Transactions on Information Forensics and Security.

[4]  Stefan Katzenbeisser,et al.  Performance and Robustness Analysis for Some Re-sampling Detection Techniques in Digital Images , 2011, IWDW.

[5]  Guna Seetharaman,et al.  Harnessing Motion Blur to Unveil Splicing , 2014, IEEE Transactions on Information Forensics and Security.

[6]  Hany Farid,et al.  Detecting Photographic Composites of People , 2008, IWDW.

[7]  Jichang Guo,et al.  Passive forensics for copy-move image forgery using a method based on DCT and SVD. , 2013, Forensic science international.

[8]  Nasir D. Memon,et al.  Image manipulation detection with Binary Similarity Measures , 2005, 2005 13th European Signal Processing Conference.

[9]  Weiyao Lin,et al.  Survey on blind image forgery detection , 2013, IET Image Processing.

[10]  Hany Farid,et al.  Exposing digital forgeries through chromatic aberration , 2006, MM&Sec '06.

[11]  V. Mankar,et al.  Blind method for rescaling detection and rescale factor estimation in digital images using periodic properties of interpolation , 2014 .

[12]  Hae-Yeoun Lee,et al.  Estimation of color modification in digital images by CFA pattern change. , 2013, Forensic science international.

[13]  G. Xiao,et al.  Erratum to “Characterization of Human Colorectal Cancer MDR1/P-gp Fab Antibody” , 2014, The Scientific World Journal.

[14]  Zhe Li,et al.  Blind Detection of Digital Forgery Image Based on the Local Entropy of the Gradient , 2008, IWDW.

[15]  Mo Chen,et al.  Imaging Sensor Noise as Digital X-Ray for Revealing Forgeries , 2007, Information Hiding.

[16]  Jiangbin Zheng,et al.  A Digital Forgery Image Detection Algorithm Based on Wavelet Homomorphic Filtering , 2008, IWDW.

[17]  Shih-Fu Chang,et al.  Image Splicing Detection using Camera Response Function Consistency and Automatic Segmentation , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[18]  Qingzhong Liu,et al.  Detection of JPEG double compression and identification of smartphone image source and post-capture manipulation , 2013, Applied Intelligence.

[19]  Nasir D. Memon,et al.  Image manipulation detection , 2006, J. Electronic Imaging.

[20]  Nenghai Yu,et al.  Doctored JPEG image detection , 2008, 2008 IEEE International Conference on Multimedia and Expo.

[21]  Min Wu,et al.  Noise Features for Image Tampering Detection and Steganalysis , 2007, 2007 IEEE International Conference on Image Processing.

[22]  Shih-Fu Chang,et al.  Camera Response Functions for Image Forensics: An Automatic Algorithm for Splicing Detection , 2010, IEEE Transactions on Information Forensics and Security.

[23]  Min Wu,et al.  Digital image forensics via intrinsic fingerprints , 2008, IEEE Transactions on Information Forensics and Security.

[24]  Jiwu Huang,et al.  A framework for identifying shifted double JPEG compression artifacts with application to non-intrusive digital image forensics , 2013, Science China Information Sciences.

[25]  Bernard H. Stark,et al.  IEEE International Conference on Industrial Informatics , 2009 .

[26]  Nasir D. Memon,et al.  Tamper Detection Based on Regularity of Wavelet Transform Coefficients , 2007, 2007 IEEE International Conference on Image Processing.

[27]  Min Wu,et al.  Nonintrusive component forensics of visual sensors using output images , 2007, IEEE Transactions on Information Forensics and Security.

[28]  S. Han,et al.  A survey of digital image watermarking techniques , 2005, INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005..

[29]  Silvano Di Zenzo,et al.  A note on the gradient of a multi-image , 1986, Comput. Vis. Graph. Image Process..

[30]  Weidong Min,et al.  Exposing Image Forgery by Detecting Consistency of Shadow , 2014, TheScientificWorldJournal.