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Demonstration of FusionNet for touchless palmprint and finger texture recognition. Based on the source code for the 2019 IEEE CIVEMSA paper "Touchless palmprint and finger texture recognition: A Deep Learning fusion approach"

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FusionNet for touchless palmprint and finger texture recognition using a webcam

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

Outline: Outline

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';

Procedure:
https://github.com/AngeloUNIMI/Demo_FusionNet/blob/master/Instructions/Demo_FusionNet%20-%20Instructions.pdf

Images:

Hand segmentation:
Outline

Palmprint ROI extraction:
Outline

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

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Demonstration of FusionNet for touchless palmprint and finger texture recognition. Based on the source code for the 2019 IEEE CIVEMSA paper "Touchless palmprint and finger texture recognition: A Deep Learning fusion approach"

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