Git Product home page Git Product logo

refnet_ijcb2021's Introduction

Orientation Field Estimation for Latent Fingerprints with Prior Knowledge of Fingerprint Pattern

We provide the clean-version training and evaluation code of our IJCB 2021 paper:

Orientation Field Estimation for Latent Fingerprints with Prior Knowledge of Fingerprint Pattern
Yongjie Duan, Jianjiang Feng, Jiwen Lu, and Jie Zhou
IJCB 2021 [ paper, highlight, presentation ]

Overview

Estimating orientation field for latent fingerprints plays a crucial role in latent fingerprints recognition systems. Considering the intrinsic characteristics of fingerprints that the distribution of orientation field varies with the fingerprint patterns, we propose an orientation field estimation algorithm for latent fingerprints based on residual learning using prior knowledge of fingerprint patterns.
Specifically, statistical distribution models of orientation field, for different fingerprint patterns, are calculated based on a large database consisting of 14,000 fingerprints with good quality using clustering method.

finger-pattern

The residual orientation fields and reliability scores, indicating the consistency with different statistical orientation models, are estimated using a deep network, named RefNet. Then the final orientation field is obtained by fusing the estimations according to their corresponding reliability scores.

overview

Enviroment

Set up Python 3.7.0 enviroment:

pytorch==1.7.0
torchvision==0.8.1
tensorboard==2.4.1

Trained Model

Our trained model (download link). Please download and unzip to the current directory as follows:

Root
└── checkpoints
    └── septype_mixhard_20201012

Results

We conducted experiments on gerprint database NIST SD27 to compare the propose algorithm with state-of-the-art orientation field estimation algorithms.
The accuracy of orientation field estimation is evaluated by the average Root Mean Square Deviation (RMSD)

Methods All Good Bad Ugly
STFT 32.51 27.27 34.10 36.36
FOMFE 28.12 22.83 29.09 32.63
GlobalDict 18.44 14.40 19.18 21.88
LocalDict 14.35 11.15 15.15 16.85
LocalDict-M 13.76 10.87 14.12 16.40
ConvNet 13.51 10.76 13.94 16.00
SparseCoding 16.38 12.57 16.88 20.22
ExSearch-B 13.54 11.21 14.20 14.95
ExSearch 13.01 10.85 13.99 14.27
FingerNet 17.82 13.67 18.42 21.50
Single 12.46 9.91 12.91 14.65
Single-M 12.20 9.65 12.73 14.39
Ours 12.16 9.87 12.83 13.85
Ours-M 12.10 9.60 12.71 14.07

Fingerprint matching experiment is applied to examine the contribution of the proposed orientation field estimation in overall fingerprint identification system. CMC curves of different algorithms on latent fingerprint database NIST SD27 as well as three subsets: (a) all (258 latents), (b) good quality (88 latents), (c) bad quality (85 latents), (d) ugly quality (85 latents). “-M” denotes manually marked fingerprint pose.

cmc_nist27

If you find this study useful for your reesearch, please cite our paper:

@inproceedings{duan2021prior,
author = {Yongjie Duan, Jianjiang Feng, Jiwen Lu, and Jie Zhou},
booktitle = {Proceedings of the IEEE International Joint Conference on Biometrics},
title = {Orientation Field Estimation for Latent Fingerprints with Prior Knowledge of Fingerprint Pattern},
year = {2021}
}

refnet_ijcb2021's People

Contributors

keyunj avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.