DocumentCode :
2726478
Title :
A new approach merging markov and DCT features for image splicing detection
Author :
Zhang, Jing ; Zhao, Yun ; Su, Yuting
Author_Institution :
Sch. of Electron. Inf. Eng., Tianjin Univ., Tianjin, China
Volume :
4
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
390
Lastpage :
394
Abstract :
Splicing detection is of fundamental importance in digital image forensics. Recent image forensic research has resulted in a number of tampering detection techniques utilizing statistical features. Fusion of multiple features provides promises for improving detection performance. In this paper, we propose a new splicing detection approach based on the features utilized for steganalysis. We merge Markov process based features and discrete cosine transform (DCT) features for splicing detection. The proposed approach can achieve an accuracy of 91.5% with a 109-dimensional feature vector. Experimental results demonstrate its superior performance over the prior arts.
Keywords :
Markov processes; discrete cosine transforms; image recognition; splicing; DCT features; digital image forensics; discrete cosine transform; features utilized steganalysis; fusion multiple features; image splicing detection; improving detection performance; new approach merging Markov; splicing detection approach; tampering detection techniques; utilizing statistical features; Digital images; Discrete cosine transforms; Feature extraction; Forensics; Markov processes; Merging; Splicing; Steganography; Support vector machine classification; Support vector machines; DCT features; Markov process; digital image forensics; splicing detection; steganalysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5357642
Filename :
5357642
Link To Document :
بازگشت