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The Effect of Physical Based Features for Recognition of Recaptured Images


Affiliations
1 Department of Computer Science, University of Jaffna, Sri Lanka
 

It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. 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. Even though, there are a number of features that have been proposed in various state-of-the art visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive features in the context of recognition of recaptured images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.

Keywords

Image Recapture Detection, Texture, HSV, Blurriness and CS-LBP.
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  • The Effect of Physical Based Features for Recognition of Recaptured Images

Abstract Views: 236  |  PDF Views: 119

Authors

S. A. A. H. Samaraweera
Department of Computer Science, University of Jaffna, Sri Lanka
B. Mayurathan
Department of Computer Science, University of Jaffna, Sri Lanka

Abstract


It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. 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. Even though, there are a number of features that have been proposed in various state-of-the art visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive features in the context of recognition of recaptured images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.

Keywords


Image Recapture Detection, Texture, HSV, Blurriness and CS-LBP.