Demonstration source code using the webcam for touchless palmprint and finger texture recognition. The algorithms used in the code are based on 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
Source code:
https://github.com/AngeloUNIMI/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:
- launch_Demo_FusionNet.m: main file
Main directories:
- ./dirDB: directory where template are stored
- ./models: directory where pretrained models are saved
Requirements:
- A webcam
The code is preconfigured to use an integrated webcam.
Change lines 51-52 of "launch_Demo_FusionNet.m" to change webcam
%cam = webcam('integrated');
%cam.Resolution = '640x480';
Images:
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 template creation algorithms in:
A. Genovese,
Source code for the 2019 IEEE CIVEMSA paper "Touchless palmprint and finger texture recognition: A Deep Learning fusion approach"
https://github.com/AngeloUNIMI/FusionNet
the segmentation algorithms in:
A. Genovese,
Source code for palmprint segmentation and ROI extraction used in the IEEE TIFS 2019 and IEEE CIVEMSA 2019 papers,
https://github.com/AngeloUNIMI/PalmSeg
and the export_fig library:
Yair Altman,
"export_fig", 2018,
https://it.mathworks.com/matlabcentral/fileexchange/23629-export_fig