Pixel-Based Image Forgery Detection: A Review

ABSTRACT With the advancement of the digital image processing software and editing tools, a digital image can be easily manipulated. The detection of image manipulation is very important because an image can be used as legal evidence, in forensics investigations, and in many other fields. The pixel-based image forgery detection aims to verify the authenticity of digital images without any prior knowledge of the original image. There are many ways for tampering an image such as splicing or copy-move, resampling an image (resize, rotate, stretch), addition and removal of any object from the image. In this paper we have discussed various pixel-based techniques for image forgery detection, mainly copy-move and splicing techniques.

[1]  Hwei-Jen Lin,et al.  Fast copy-move forgery detection , 2009 .

[2]  Judith Redi,et al.  Digital image forensics: a booklet for beginners , 2010, Multimedia Tools and Applications.

[3]  Tiegang Gao,et al.  A robust detection algorithm for copy-move forgery in digital images. , 2012, Forensic science international.

[4]  Jing Zhang,et al.  A new approach for detecting Copy-Move forgery in digital images , 2008, 2008 11th IEEE Singapore International Conference on Communication Systems.

[5]  Luo Wei,et al.  Robust Detection of Region-Duplication Forgery in Digital Image , 2007 .

[6]  W. Marsden I and J , 2012 .

[7]  J Granty Regina Elwin,et al.  Survey on passive methods of image tampering detection , 2010, 2010 International Conference on Communication and Computational Intelligence (INCOCCI).

[8]  Li Kang,et al.  Copy-move forgery detection in digital image , 2010, 2010 3rd International Congress on Image and Signal Processing.

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

[10]  H. Farid A Survey of Image Forgery Detection , 2008 .

[11]  Yu Zhang,et al.  Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm , 2008, 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application.

[12]  Wang Zhi-quan,et al.  Fast and Robust Forensics for Image Region-duplication Forgery , 2009 .

[13]  Alberto Del Bimbo,et al.  Ieee Transactions on Information Forensics and Security 1 a Sift-based Forensic Method for Copy-move Attack Detection and Transformation Recovery , 2022 .

[14]  Ahmad Faraahi,et al.  DWT-DCT (QCD) based copy-move image forgery detection , 2011, 2011 18th International Conference on Systems, Signals and Image Processing.

[15]  Xunyu Pan,et al.  Region Duplication Detection Using Image Feature Matching , 2010, IEEE Transactions on Information Forensics and Security.

[16]  H. Farid,et al.  Image forgery detection , 2009, IEEE Signal Processing Magazine.

[17]  Jessica Fridrich,et al.  Detection of Copy-Move Forgery in Digital Images , 2004 .

[18]  Zhiquan Wang,et al.  Fast and Robust Forensics for Image Region-duplication Forgery: Fast and Robust Forensics for Image Region-duplication Forgery , 2010 .

[19]  Qiong Wu,et al.  A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries Based on DWT and SVD , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[20]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[21]  Chi-Keung Tang,et al.  Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis , 2009, Pattern Recognit..

[22]  XiaoBing Kang,et al.  Identifying Tampered Regions Using Singular Value Decomposition in Digital Image Forensics , 2008, 2008 International Conference on Computer Science and Software Engineering.

[23]  Jiwu Huang,et al.  Detect Digital Image Splicing with Visual Cues , 2009, Information Hiding.

[24]  Yogesh Rathore,et al.  DWT Based Copy-Move Image Forgery Detection , 2012 .

[25]  Shinfeng D. Lin,et al.  An integrated technique for splicing and copy-move forgery image detection , 2011, 2011 4th International Congress on Image and Signal Processing.