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.
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Tiwari, M., Gupta, B. (2019). Enhancing Source Camera Identification Using Weighted Nuclear Norm Minimization De-Noising Filter. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 760. Springer, Singapore. https://doi.org/10.1007/978-981-13-0344-9_24
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DOI: https://doi.org/10.1007/978-981-13-0344-9_24
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