scholarly journals Color Channel Characteristics (CCC) for Efficient Digital Image Forensics

2018 ◽  
Vol 8 (1) ◽  
pp. 2555-2561
Author(s):  
S. Gupta ◽  
N. Mohan
Keyword(s):  
Digital Image ◽  
Low Cost ◽  
Texture Features ◽  
Image Forensics ◽  
Digital Image Forensics ◽  
Support Vector ◽  
Image Splicing ◽  
Color Channel ◽  
Channel Characteristics ◽  
Edge Detectors

Digital image forgery has become extremely easy as low-cost image processing programs are readily available. Digital image forensics is a science of classifying images as authentic or manipulated. This paper aims at implementing a novel digital image forensics technique by exploiting an image’s Color Channel Characteristics (CCC). The CCCs considered are the noise and edge characteristics of the image. Averaging, median, Gaussian and Wiener filters along with Sobel, Canny, Prewitt and Laplacian of Gaussian (LoG) edge detectors are applied to get the noise and texture features. A complete, no reference, blind classifier for image tamper detection has been proposed and implemented. The proposed CCC classifier can detect copy-move as well as image splicing accurately with lower dimensionality. Support Vector Machine is used for classification of images as authentic or tampered. Experimental results have shown that the proposed technique outperforms the existing ones and may serve as a complete tool for digital image forensics.

Recaptured Image Forensics Algorithm Based on Image Texture Feature

2019 ◽  
Vol 34 (03) ◽  
pp. 2054011
Author(s):  
Yanjun Sun ◽  
Xuanjing Shen ◽  
Changming Liu ◽  
Yongzhe Zhao
Keyword(s):  
Digital Image ◽  
Rapid Development ◽  
Image Forensics ◽  
Detection Algorithm ◽  
Digital Image Forensics ◽  
Image Texture ◽  
Support Vector ◽  
Gray Level ◽  
Identification Rate ◽  
Occurrence Matrix

With the rapid development of digital phones, the digital image forensics system in current times has had a great impact. It will lead to a serious threat for us, and especially the emergence of the recaptured image makes the existing digital image forensics algorithm invalid. So, it needs an effective image detection algorithm for us to identify recaptured images. In this paper, a new detection algorithm of the recaptured image is presented based on gray level co-occurrence matrix by analyzing the differences between the real and recaptured images. In order to analyze the differences, a new image evaluation model was put forward in this paper, which is called image variance ratio. Firstly, the algorithm proposed extracted high-frequency and low-frequency information of images by wavelet transform, based on which we calculated the relative gray level co-occurrence matrices. Secondly, the features of gray level co-occurrence matrix were extracted. At last, the recaptured image was classified by the support vector machine according to the features. The experimental results showed the algorithm proposed can not only effectively identify the recaptured image obtained from different media but also have better identification rate.

A Survey of Blind Digital Image Forensics Technology for Authenticity Detection

2009 ◽  
Vol 34 (12) ◽  
pp. 1458-1466 ◽  
Author(s):  
Qiong WU ◽  
Guo-Hui LI ◽  
Dan TU ◽  
Shao-Jie SUN
Keyword(s):  
Digital Image ◽  
Image Forensics ◽  
Digital Image Forensics

A survey of passive technology for digital image forensics

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

scholarly journals A Scaling Robust Copy-Paste Tampering Detection for Digital Image Forensics

2016 ◽  
Vol 79 ◽  
pp. 458-465 ◽  
Author(s):  
Anil Dada Warbhe ◽  
R.V. Dharaskar ◽  
V.M. Thakare
Keyword(s):  
Digital Image ◽  
Image Forensics ◽  
Digital Image Forensics ◽  
Tampering Detection

Digital Image Forensics Using Multi-Resolution Histograms

2012 ◽  
pp. 163-175
Author(s):  
Jin Liu ◽  
Hefei Ling ◽  
Fuhao Zou ◽  
WeiQi Yan ◽  
Zhengding Lu
Keyword(s):  
Digital Image ◽  
Image Forensics ◽  
Experimental Results ◽  
Digital Image Forensics ◽  
Clone Detection ◽  
Splicing Detection

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.

scholarly journals Digital image forensics via intrinsic fingerprints

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

The Impact of Exposure Settings in Digital Image Forensics

2018 ◽  
Author(s):  
Li Lin ◽  
Wenhao Chen ◽  
Yangxiao Wang ◽  
Stephanie Reinder ◽  
Yong Guan ◽  
...  
Keyword(s):  
Digital Image ◽  
Image Forensics ◽  
Digital Image Forensics ◽  
The Impact
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