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Vol. 161, Issue 12, December 2013, pp. 92-97

 

Bullet

 

Copy-Paste Forgery Image Blind Detection Algorithm Based on Histogram Invariant Moments
 
1 Junliu ZHONG, 2 Yanfen GAN

1 College of Information Engineering, Guangdong Mechanical & Electrical College, Guangzhou, China

2 Information Science and Technology Department Guangdong University of Foreign Studies South China Business College, Guangzhou, China

1 Tel.: +8615013207300

1 E-mail:286777680@qq.com

 

Received: 16 September 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems

 

Abstract: Considered that general detection algorithms against common copy-paste image forgery have poor robustness, this paper proposes a forgery image blind detection algorithm based on histogram invariant moments. The algorithm first carries out discrete wavelet transform on the image to be detected to extract low frequency part, then divides the low-frequency image into blocks. After that, histogram invariant moments characteristic vectors of these blocks are extracted and a characteristic matrix is constructed using these vectors. The characteristic vectors in the matrix are sorted by dictionary, and finally the sorted adjacent blocks. The block is judged by confidence distance to determine whether some of them are copy-paste image blocks. Experiments show that the proposed algorithm can more accurately locate the forged area of copy-paste images, and has better robustness on anti-noise, anti-compression, anti-rotation and anti-scaling. Meanwhile, the amount of computation is effectively reduced and detection efficiency is improved.

 

Keywords: Histogram invariant moments, Discrete wavelet, Image matching, Image forgery.

 

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