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PRNU-Based Forgery Localization in a Blind Scenario

  • Davide Cozzolino
  • Francesco Marra
  • Giovanni Poggi
  • Carlo Sansone
  • Luisa Verdoliva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10485)

Abstract

The Photo Response Non-Uniformity (PRNU) noise can be regarded as a camera fingerprint and used, accordingly, for source identification, device attribution and forgery localization. To accomplish these tasks, the camera PRNU is typically assumed to be known in advance or reliably estimated. However, there is a growing interest for methods that can work in a real-word scenario, where these hypotheses do not hold anymore. In this paper we analyze a PRNU-based framework for forgery localization in a blind scenario. The framework comprises four main steps: PRNU-based blind image clustering, parameter estimation, device attribution, and forgery localization. Each of these steps impacts on the final outcome of the analysis. The aim of this paper is to assess the overall performance of the proposed framework and how it depends on the individual steps.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Davide Cozzolino
    • 1
  • Francesco Marra
    • 1
  • Giovanni Poggi
    • 1
  • Carlo Sansone
    • 1
  • Luisa Verdoliva
    • 1
  1. 1.DIETI - University of Naples Federico IINaplesItaly

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