Title :
Image tampering detection based on stationary distribution of Markov chain
Author :
Wang, Wei ; Dong, Jing ; Tan, Tieniu
Author_Institution :
Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China
Abstract :
In this paper, we propose a passive image tampering detection method based on modeling edge information. We model the edge image of image chroma component as a finite-state Markov chain and extract low dimensional feature vector from its stationary distribution for tampering detection. The support vector machine (SVM) is utilized as classifier to evaluate the effectiveness of the proposed algorithm. The experimental results in a large scale of evaluation database illustrates that our proposed method is promising.
Keywords :
Markov processes; edge detection; feature extraction; image classification; image colour analysis; support vector machines; SVM; edge information modeling; finite-state Markov chain; image chroma component; image classifier; image tampering detection; low dimensional feature vector; stationary distribution; support vector machine; Color; Databases; Feature extraction; Image edge detection; Markov processes; Pixel; Splicing; Markov chain; image chroma; stationary distribution; tampering detection;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5652660