Matlab source code for the paper:
A. Genovese, V. Piuri, F. Scotti, and S. Vishwakarma,
"Touchless palmprint and finger texture recognition: A Deep Learning fusion approach",
in Proc. of the 2019 IEEE Int. Conf. on Computational Intelligence & Virtual Environments for Measurement Systems and Applications (CIVEMSA 2019),
Tianjin, China, June 14-16, 2019, pp. 1-6.
ISBN: 978-1-5386-8344-6. DOI: 10.1109/CIVEMSA45640.2019.9071620
Paper:
https://ieeexplore.ieee.org/document/9071620
Project page:
http://iebil.di.unimi.it/fusionnet/index.htm
Outline:
Demo:
https://github.com/AngeloUNIMI/Demo_FusionNet
Citation:
@InProceedings {civemsa19,
author = {A. Genovese and V. Piuri and F. Scotti and S. Vishwakarma},
booktitle = {Proc. of the 2019 IEEE Int. Conf. on Computational Intelligence & Virtual Environments
for Measurement Systems and Applications (CIVEMSA 2019)},
title = {Touchless palmprint and finger texture recognition: A Deep Learning fusion approach},
address = {Tianjin, China},
month = {June},
day = {14-16},
year = {2019},
pages = {1-6},
}
Main files:
- main_FusionNet.m: main file
Required files:
- ./images/DB Fusion Palm-Knuckle (orig)/REST_hand_database:
Database of images downloaded from: http://www.regim.org/publications/databases/regim-sfax-tunisian-hand-database2016-rest2016/
The structure of the folders must be:
"images/DB Fusion Palm-Knuckle (orig)/REST_hand_database/p1"
"images/DB Fusion Palm-Knuckle (orig)/REST_hand_database/p2"
etc.
Part of the code uses the Matlab source code of the paper:
- T. Chan, K. Jia, S. Gao, J. Lu, Z. Zeng and Y. Ma, "PCANet: A Simple Deep Learning Baseline for Image Classification?," in IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5017-5032, Dec. 2015. DOI: 10.1109/TIP.2015.2475625 http://mx.nthu.edu.tw/~tsunghan/Source%20codes.html
the VLFeat library:
- A. Vedaldi and B. Fulkerson, "VLFeat: An Open and Portable Library of Computer Vision Algorithms", 2008, http://www.vlfeat.org
and the functions by Peter Kovesi:
- Peter Kovesi, "MATLAB and Octave Functions for Computer Vision and Image Processing", https://www.peterkovesi.com/matlabfns
The database used in the paper can be obtained at: