Noiseprint: a CNN-based camera model fingerprint

Noiseprint is a CNN-based camera model fingerprint extracted by a fully Convolutional Neural Network (CNN).

License

Copyright (c) 2019 Image Processing Research Group of University Federico II of Naples ('GRIP-UNINA').

All rights reserved.

This software should be used, reproduced and modified only for informational and nonprofit purposes.

By downloading and/or using any of these files, you implicitly agree to all the terms of the license, as specified in the document LICENSE.txt (included in this package)

Installation

The code requires Python 3.x and Tensorflow 1.2.1 .

To install Python 3.x for Ubuntu, you can run:

apt-get update
apt-get install -y python3.5 python3.5-dev python3-pip python3-venv

We recommend to use a virtual environment:

python3.5 -m venv ../venv
source ../venv/bin/activate
pip install --upgrade pip

Installation with GPU

Install Cuda8 and Cudnn5, more informetion on sites:

• https://developer.nvidia.com/cuda-downloads
• https://developer.nvidia.com/cudnn

Then install the requested libraries using:

cat noiseprint/requirements-gpu.txt | xargs -n 1 -L 1 pip install

Installation without GPU

Install the requested libraries using:

cat noiseprint/requirements-cpu.txt | xargs -n 1 -L 1 pip install

Usage

To extract the noiseprint, run:

python main_extraction.py <input image> <output mat/npz file>

The noiseprint is saved in a file with extension mat or npz. To show the saved noiseprint, run:

python main_showout.py <input image> <output mat/npz file>

While to execute the blind localization method, run:

python main_blind.py <input image> <output mat/npz file>

The heatmap is saved in a file with extension mat or npz. To show the result, run:

python main_showres.py <input image> <gt image> <output mat/npz file>

To convert the heatmap in a png image, run:

python main_map2uint8.py <output mat/npz file> <output png file>

Demo

To execute the demo, run the script

cd ./demo
./demo_extraction.sh
./demo_heatmap.sh

Reference

@article{Cozzolino2019_Noiseprint,
  title={Noiseprint: A CNN-Based Camera Model Fingerprint},
  author={D. Cozzolino and L. Verdoliva},
  journal={IEEE Transactions on Information Forensics and Security},
  doi={10.1109/TIFS.2019.2916364},
  pages={144-159},
  year={2020},
  volume={15}
}