Open AccessImage forgery detection in contourlet transform domain based on new chaotic cellular automata
Author(s) -
Barani Milad Jafari,
Ayubi Peyman,
Jalili Fooad,
Valandar Milad Yousefi,
Azariyun Ehsan
Publication year - 2015
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0122
pISSN - 1939-0114
DOI - 10.1002/sec.1365
Subject(s) - computer science , cellular automaton , authentication (law) , randomness , artificial intelligence , image (mathematics) , contourlet , chaotic , pattern recognition (psychology) , false alarm , digital watermarking , discrete cosine transform , computer vision , computer security , wavelet transform , wavelet , mathematics , statistics
Image authentication includes techniques that detect unauthorized changes in digital pictures. Image authentication is generally categorized into two primary categories, active and passive methods. In this paper, a new active image authentication method is proposed for tamper detection based on contourlet transform. Cellular automata and ‘Game of Life’ are also used to improve the detection of tampered area. A pseudo‐random number generator based on cellular automata has been used to improve security of proposed technique. We evaluates security and randomness of proposed pseudo‐random number generator using by NIST statistical test suite. Experimental results show that the proposed method is sensitive to any tampers, and it can detect forged areas of the images. Visual quality of image after embedding process is desirable due to Peak Signal‐to‐Noise Ratio (PSNR) measure. Copyright © 2015 John Wiley & Sons, Ltd.