S.A.A.H. Samaraweera and B. Mayurathan, University of Jaffna, Sri Lanka

With the development of multimedia technology and digital devices, it is very simple and easier to recapture a high quality images from LCD screens. In authentication, the use of such recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Image recapture detection (IRD) is to distinguish realscene images from the recaptured ones. An image recapture detection method based on set of physical based features is proposed in this paper, which uses combination of low-level features including texture, HSV colour and blurriness. Twenty six dimensions of features are extracted to train a support vector machine classifier with linear kernel. The experimental results show that the proposed method is efficient with good recognition rate of distinguishing real scene images from the recaptured ones. The proposed method also possesses low dimensional features compared to the state-of-the-art recaptured methods.

Image Recapture Detection, Texture, HSV, Blurriness & Support Vector Machine