Publication 2018 April

Real Time Source Camera Identification using Advanced Blind Source Separation Method

Sneha K A, Delna K V ,Aneesh R P  

 

 

Abstract - In today’s digitalizing world, multimedia devices and software have an important role in our lives. Particularly multi-media devices like digital camera and smart phones. Since people use them for illegal purpoe, a safety measure is essential against them. An efficient digital camera identification algorithm based on Sensor Pattern Noise (SPN) is proposed in this paper. Sensor pattern noise is a unique noise found in digital cameras. The huge information that a sensor pattern noise holds in terms of the frequency makes it unique, because of this uniqueness the SPN is suitable for source camera identification .ICA(Independent Component Analysis) algorithm is used for separating the sensor pattern from the image. Cameras are classified according to the standard deviation of sensor pattern noises of camera. The system is implemented in Raspberry Pi with python and openCV. The algorithm is tested with the imaging dataset containing 250 images of 10 different camera models. The system is successfully implemented in real time application with Pi cam and Web cam..

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Keywords

Sensor Pattern Noise, ICA (Independent Com-ponent Analysis), Source camera detection, Raspberry Pi.


 

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Authors :

Sneha K A

SCET Kerala

Delna K V

SCET Kerala

Aneesh.R.P

Regional center IHRD, Thiruvananthapuram

  


Copy Right 2017 -These are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 
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