FLoRIN for Iris Segmentation

This repository contains the code used in the paper "Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples" published at the 2019 International Conference on Biometrics, Crete, Greece.

Pre-print available at: https://arxiv.org/abs/1901.01575

Dependencies

To run this code, the following dependencies must be met.

FLoRIN

• Python 3.4+
• numpy
• scipy
• scikit-image
• h5py

OSIRIS

• gcc
• Python 3.4+
• OpenCV 2.14

SegNet

• MATLAB r2018b (or newer)

Preparation

1. Download and install OSIRIS v4.1. A local copy of OSIRIS is also included into this repository (./matching/OSIRIS_v4.1). To reproduce this work, compile with GCC 7.1.0 following the OSIRIS installation instructions.
2. Download and install MATLAB.
3. Download and install Python 3.4+. To reproduce this work, install Python 3.6.4 compiled with GCC 7.1.0.
4. Request a copy of the [Warsaw-BioBase-Pupil-Dynamics-v3 dataset](http://zbum.ia.pw.edu.pl/EN/node/46 "Warsaw Biobase Pupil Dynamics v3 Dataset).

Segmentation

In a terminal, run

bash segment_and_time.sh /path/to/dataset /path/to/florin/virtual/environment /path/to/osiris/install

This script will attempt to install FLoRIN and its dependencies in a virtual environment, prepare the dataset and configuration files, and run all of the segmentation and timing code used to compare FLoRIN, OSIRIS, and SegNet in sequence.

Matching

1. Put the segmentation masks (either FLoRIN- or SegNet-based) into ./matching/imageData/Warsaw-BioBase-Pupil-Dynamics-v3-segmentation-masks folder
2. Compile OSIRIS (you will need to edit the makefile accordingly to your system configuration). Note that OSIRIS requires OpenCV 2.4.x correctly installed. The executable osiris file should appear in matching/OSIRIS_v4.1/src folder.
3. Open Matlab, go to the folder with icb2019.m m-file and run it. This m-file calls other scripts that go through the process step by step. The entire process may take more than an hour, depending on your hardware.
4. The matching scores should appear in the matchingResults folder as res_matching_genuine.txt and res_matching_impostor.txt.

Ofiicial FLoRIN Software

The official FLoRIN software release is now available as a pip-installable Python package! We are currently working on translating the FLoRIN pipeline used in this study to the new code and will update the repository when it is ready. To get FLoRIN for yourself, install Python 3.4+ and run

pip install florin

This code is under active development, and we welcome any contributions from the community.