Title :
Resampling Tamper Detection Based on JPEG Double Compression
Author :
Dan Zhu ; Zhiping Zhou
Author_Institution :
Sch. of Internet of Things Eng., Jiangnan Univ., Wuxi, China
Abstract :
JPEG compression and resampling operations appear frequently when image is tampered, hence the traces of JPEG compression and resampling are used to detect images. As JPEG compression and resampling operations affect the linear correlation between coefficients, so the traces of JPEG compression and the linear correlation are introduced when images are resampled and saved in JPEG format. Hence, the moment of DCT coefficient histogram are taken as the factor of JPEG compression, and due to the singular value decomposition can measure linear correlation between pixels well so that the mean value and variance of the singular values are extracted. At last, two types of features are extracted and trained by SVM. Experimental results show that proposed method has a good detection rate for resampling compression images, especially for rotation operation and the scale factor which greater than 1.
Keywords :
data compression; discrete cosine transforms; feature extraction; image coding; singular value decomposition; support vector machines; DCT coefficient histogram; JPEG double compression; JPEG resampling; SVM; compression images; feature extraction; linear correlation; mean value; scale factor; singular value decomposition; singular value variance; tamper detection resampling; Discrete cosine transforms; Feature extraction; Histograms; Image coding; Q-factor; Quantization (signal); Transform coding; JPEG compression; image forgery; resampling detection; singular value decomposition; support vector machine;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2014 Fourth International Conference on
Conference_Location :
Bhopal
Print_ISBN :
978-1-4799-3069-2
DOI :
10.1109/CSNT.2014.188