Analysis of Image Inconsistency Based on Discrete Cosine Transform (DCT)

The popularity of Digital Image has widely increased in society. Nowadays, by the easy availability of image editing software people can manipulate the image for malicious intent. Our proposed method is to detect inconsistency in the exact area of an image. The paper involves different steps, i.e., preprocessing, feature extraction, and matching processes. In feature extraction, we apply Discrete Cosine Transform (DCT). Evaluate our system by calculating True Positive Rate (TPR), False Positive Rate (FPR), and Area Under the Curve (AUC) of 0.3372, 0.5278, and 0.949, respectively. The results show more efficiency.

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

[2]  Vijay H. Mankar,et al.  Digital image forgery detection using passive techniques: A survey , 2013, Digit. Investig..

[3]  Minerva M. Yeung,et al.  Digital watermarking , 1998, CACM.

[4]  Kevin Curran,et al.  Digital image steganography: Survey and analysis of current methods , 2010, Signal Process..

[5]  Jean-Luc Dugelay,et al.  A Survey of Watermarking Algorithms for Image Authentication , 2002, EURASIP J. Adv. Signal Process..

[6]  Pravin Yannawar,et al.  Image inconsistency detection using histogram of orientated gradient (HOG) , 2017, 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM).

[7]  Charles Elkan,et al.  Using the Triangle Inequality to Accelerate k-Means , 2003, ICML.

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

[9]  Zhen Zhang,et al.  A survey on passive-blind image forgery by doctor method detection , 2008, 2008 International Conference on Machine Learning and Cybernetics.

[10]  Pravin Yannawar,et al.  Image Inconsistency Detection Using Local Binary Pattern (LBP) , 2017 .

[11]  Noura A. Semary,et al.  A proposed accelerated image copy-move forgery detection , 2014, 2014 IEEE Visual Communications and Image Processing Conference.

[12]  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.

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

[14]  Ajaz Hussain Mir,et al.  Digital Image Forgeries and Passive Image Authentication Techniques: A Survey , 2014 .

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

[16]  Chien-Ping Chang,et al.  Detection of copy-move image forgery using histogram of orientated gradients , 2015, Inf. Sci..

[17]  Babak Mahdian,et al.  Ieee Transactions on Information Forensics and Security 1 Blind Authentication Using Periodic Properties of Interpolation , 2022 .