Analysis of Benford's law in digital image forensics

Author(s):  
Neetu Singh ◽  
Rishab Bansal
2009 ◽  
Vol 34 (12) ◽  
pp. 1458-1466 ◽  
Author(s):  
Qiong WU ◽  
Guo-Hui LI ◽  
Dan TU ◽  
Shao-Jie SUN

2007 ◽  
Vol 1 (2) ◽  
pp. 166-179 ◽  
Author(s):  
Weiqi Luo ◽  
Zhenhua Qu ◽  
Feng Pan ◽  
Jiwu Huang

2016 ◽  
Vol 79 ◽  
pp. 458-465 ◽  
Author(s):  
Anil Dada Warbhe ◽  
R.V. Dharaskar ◽  
V.M. Thakare

Author(s):  
Jin Liu ◽  
Hefei Ling ◽  
Fuhao Zou ◽  
WeiQi Yan ◽  
Zhengding Lu

In this paper, the authors investigate the prospect of using multi-resolution histograms (MRH) in conjunction with digital image forensics, particularly in the detection of two kinds of copy-move manipulations, i.e., cloning and splicing. To the best of the authors’ knowledge, this is the first work that uses the same feature in both cloning and splicing forensics. The experimental results show the simplicity and efficiency of using MRH for the purpose of clone detection and splicing detection.


Author(s):  
Xi Zhao ◽  
Anthony T.S. Ho ◽  
Yun Q. Shi

In the past few years, semi-fragile watermarking has become increasingly important to verify the content of images and localise the tampered areas, while tolerating some non-malicious manipulations. In the literature, the majority of semi-fragile algorithms have applied a predetermined threshold to tolerate errors caused by JPEG compression. However, this predetermined threshold is typically fixed and cannot be easily adapted to different amounts of errors caused by unknown JPEG compression at different quality factors (QFs). In this paper, the authors analyse the relationship between QF and threshold, and propose the use of generalised Benford’s Law as an image forensics technique for semi-fragile watermarking. The results show an overall average QF correct detection rate of approximately 99%, when 5%, 20% and 30% of the pixels are subjected to image content tampering and compression using different QFs (ranging from 95 to 65). In addition, the authors applied different image enhancement techniques to these test images. The proposed image forensics method can adaptively adjust the threshold for images based on the estimated QF, improving accuracy rates in authenticating and localising the tampered regions for semi-fragile watermarking.


Author(s):  
Guorui Sheng ◽  
Tiegang Gao

Seam-Carving is widely used for content-aware image resizing. To cope with the digital image forgery caused by Seam-Carving, a new detecting algorithm based on Benford's law is presented. The algorithm utilize the probabilities of the first digits of quantized DCT coefficients from individual AC modes to detect Seam-Carving images. The experimental result shows that the performance of proposed method is better than that of the method based on traditional Markov features and other existing methods.


2008 ◽  
Vol 3 (1) ◽  
pp. 101-117 ◽  
Author(s):  
Ashwin Swaminathan ◽  
Min Wu ◽  
K.J. Ray Liu

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