All Projects → AngeloUNIMI → Palmnet

AngeloUNIMI / Palmnet

Licence: gpl-3.0
Source code for the 2019 IEEE TIFS paper "PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition"

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PalmNet

Matlab source code for the paper:

A. Genovese, V. Piuri, K. N. Plataniotis, and F. Scotti,
"PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition",
IEEE Transactions on Information Forensics and Security, 2019.
DOI: 10.1109/TIFS.2019.2911165
https://ieeexplore.ieee.org/document/8691498

Project page:

http://iebil.di.unimi.it/palmnet/index.htm

Outline: Outline

Citation:

@Article{tifs19,
	author = {A. Genovese and V. Piuri and K. N. Plataniotis and F. Scotti},
	title = {PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition},
	journal = {IEEE Transactions on Information Forensics and Security},
	volume={14}, 
	number={12}, 
	pages={3160-3174}, 
	doi={10.1109/TIFS.2019.2911165}, 
	ISSN={1556-6013}, 
	month={December},}

Main files:

  • launch_PalmNet.m: main file
  • ./params/paramsPalmNet.m: parameter file

Required files:

  • ./images: Database of images, with filenames in the format "NNNN_SSSS.ext", where NNNN is the 4-digit individual id, SSSS is the 4-digit sample id, and ext is the extension.
    For example: "0001_0001.bmp" is the first sample of the first individual. In the paper, left and right palms of the same person are considered as different individuals.

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:

The databases used in the paper can be obtained at:

The segmentation algorithm can be found at:

https://github.com/AngeloUNIMI/PalmSeg

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