• Introduction
• Database
• Inference
• Models
• Getting Started (Documentation)
• License
• Citing

This repository contains the code and a pre-generated dataset associated with the paper "SpoofGAN: Synthetic Fingerprint Spoof Images".

A preprepared dataset of synthetic fingerprints (live and 6 spoof types) is available for download at this link: http://biometrics.cse.msu.edu/Publications/Databases/MSU_SpoofGAN/. There are 1,500 unique fingers with 3 live impressions and 3 impressions of each spoof type, giving a total of 31,500 images.

To generate synthetic images run the generate.py script with the appropriate arguments.

CUDA_VISIBLE_DEVICES=0 python generate.py --material --output_dir --num_fingers --num_impressions --seed --start --random_ckpt

Arguments:
	--material: Material type to generate. Default='live'.
	--output_dir: Output save directory. Default='output'.
	--num_fingers: Number of unique finger IDs to generate. Default=10.
	--num_impressions: Number of impressions per finger. Default=3
	--seed: Random Seed. Default=12.
	--start: Starting finger ID. Default=0.
	--random_ckpt: Load random model ckpt rather than latest. Default=False.

Example:

CUDA_VISIBLE_DEVICES=0 python generate.py --material ecoflex --output_dir output --num_fingers 10 --num_impressions 3

The list of possible materials to choose from is given below:

live
pa
body_double
conductive_ink
ecoflex
gelatin
gummy_overlay
playdoh
tattoo

All model checkpoints can be found at https://drive.google.com/drive/folders/1ntdAwUJzFuozTqonaoxGlt7NNhCGB6pe?usp=sharing.

In order for the inference script to run, the model checkpoint folders (i.e., log folders) must be downloaded and placed in the master_print_generator and renderer directories.

Creating conda environment

conda create -n (name) python=3.7

Install the following packages:

conda install tensorflow-gpu==1.14.0
pip install opencv-python
conda install gast==0.2.0
conda install scipy==1.2.1
conda install pillow==8.4.0
conda install tqdm

This code is provided under a Creative Commons Attribution-NonCommercial (CC BY-NC) license.

Copyright (c) [2022] [Steven A. Grosz]

If you use this code in your work please cite the following paper:

S.A. Grosz and A. K. Jain, "SpoofGAN: Synthetic Fingerprint Spoof Images," IEEE Transactions on Information Forensics and Security, 2022.