Digital image forgery detection using artificial neural network and independent component analysis

被引:14
作者
Gopi, E. S. [1 ]
机构
[1] Natl Inst Technol, Dept Elect & Commun Engn, Tiruchirappalli 620015, Tamil Nadu, India
关键词
auto regressive model; back propagation neural network;
D O I
10.1016/j.amc.2007.04.055
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Digital image forgery is the process of manipulating the original photographic images like resizing, rotation, scaling, etc. To produce the photographic images as the evidence to the court, there is the need to identify whether the produced image is original or forgery image. In this paper, an attempt is made to detect forgery portions of the digital image. This is achieved by training the artificial neural network using the ICA coefficients obtained in the AR domain of the image data. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:540 / 543
页数:4
相关论文
共 4 条
[1]  
GOPI ES, 2006, IEEE P CAN C EL COMP, P194
[2]  
Haykin S., 1999, Neural networks: a comprehensive foundation, V2nd ed.
[3]   Independent component analysis:: algorithms and applications [J].
Hyvärinen, A ;
Oja, E .
NEURAL NETWORKS, 2000, 13 (4-5) :411-430
[4]   Exposing digital forgeries by detecting traces of resampling [J].
Popescu, AC ;
Farid, H .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2005, 53 (02) :758-767