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Enhancing Source Camera Identification Using Weighted Nuclear Norm Minimization De-Noising Filter

  • Mayank Tiwari
  • Bhupendra GuptaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 760)

Abstract

Photo-response non-uniformity noise (PRNU) is widely accepted as fingerprint (FP) of digital camera. However, extraction of PRNU from given images is still a challenging task. In the previous literature, number of de-noising filters has been used for PRNU extraction. However, it is observed that PRNU extracted by existing de-noising filters contains high-frequency (edges and texture) details of the image. This increases false rejection rate in source camera identification (SCI) process. In this work, we have used weighted nuclear norm minimization (WNNM)-based de-noising filter for PRNU extraction. The PRNU extracted by WNNM-based de-noising filter contains least amount of scene details. Experimental results demonstrate the proposed method outperforms, or at least performs comparably to, the state-of-the-art methods.

Keywords

Digital image forensics Photo-response non-uniformity noise Source camera identification 

Notes

Acknowledgements

Authors thank [19, 20] for many helpful suggestions and sharing of their MATLAB code with us.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of MathematicsIndian Institute of Information Technology, Design & ManufacturingJabalpurIndia

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