Authors:
Megha Borole,Prof. S. R. Kolhe,DOI NO:
https://doi.org/10.26782/jmcms.2019.02.00004Keywords:
Camera identification,photo response non-uniformity (PRNU),Krawtchouk moments,fuzzy min-max neural networkwith compensatory neuron (FMCN),Abstract
In late years, camera identification methods have drawn attention in the area of digital forensics. To detect the source camera through which the picture is caught, Photo-Response Non uniformity (PRNU) noise is utilized as a camera, impression, as it is a particular component that recognizes pictures taken from the comparable cameras. This paper introduces a camera identification technique which is based on Krawtchouk Moment invariant features. The Photo Response Non-Uniformity (PRNU) noise is a type of sensor finger impression, which permits to extraordinarily distinguish the camera that took an image. It is estimated from the denoised images using a denoised filter. Then estimate the Krawtchouk Moment invariants from the PRNU noise pattern. The Krawtchouk Moments are invariant to scaling, translation, rotation, and shear. These invariants are fed to Fuzzy Min-Max Neural Network with Compensatory Neuron (FMCN) and by performing ten-fold cross-validation technique, verification is made out. The experimental results show that the proposed technique achieves an average accuracy of 93.3% for first experiment and 98.3% for the second experiment.Refference:
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Megha Borole, Prof. S. R. Kolhe View Download