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Forensic Reconstruction of Severely Degraded License Plates

Code and pretrained Real-world CNN model for:

Benedikt Lorch, Shruti Agarwal, Hany Farid. Forensic Reconstruction of Severely Degraded License Plates. Media Watermarking, Security, and Forensics 2019, Burlingame, CA, USA, MWSF-529. bibtex

Getting Started

Tested on Ubuntu 16.04 with Python 3.5, TensorFlow 1.4.0 and 1.10.1.

Installation

Clone this repo.

git clone https://github.com/btlorch/license-plates.git
cd license-plates

Inside your virtual environment install required packages.

pip install -r requirements.txt

Download trained model to <repo>/model or a directory of your choice.

wget https://faui1-files.cs.fau.de/public/mmsec/lorch/license-plates/license-plates-trained-model.zip
unzip license-plates-trained-model.zip -d model

Running the demo

cd src
jupyter notebook

Then open demo.ipynb.

Depending on the location of the trained weights, you may need to update the path in the first cell.

Examples

North Carolina license plate

Arizona license plate

Vermont license plate

CNN architecture

(View image to enlarge)

CNN architecture

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Forensic Reconstruction of Severely Degraded License Plates, Electronic Imaging, 2019.

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