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Towards Palmprint Verification On Smartphones Yingyi Zhang1,2, Lin Zhang1,*, Ruixin Zhang2, Shaoxin Li2, Jilin Li2, and Feiyue Huang2 1School of Software Engineering, Tongji University 2YoutuLab Tencent |
Introduction
This is the website for our paper "Towards Palmprint Verification On Smartphones (IEEE Trans. Image Processing, submitted)".
Tongji Mobile Palmprint Dataset
MPD contains original palm image set and generated datasets. The sturcture of our dataset is like below:
|
Dataset Name |
Description |
Number of samples |
File path |
|
PalmSet |
Original palm image set. |
16000 |
MPDv2/original palms/ |
|
MPDD |
Generated dataset for keypoint detection, in VOC format. |
366816 |
MPDv2/generation/1-keypoint_detection/ |
|
ROI |
Generated dataset of palmprint verification. |
16000 |
MPDv2/generation/2-ROI_verification/ |
PalmSet: The images in original palm dataset were palm images from built-in camera of mobile phones (Huawei/Xiaomo). The palm images are collected by mobile phones in 2 periods with various background and lighting conditions. This dataset contains 16000 palmprint images from 200 sessions (400 different hands). 10 photos of one’s hand with each phones and each time period are preserved in this dataset. All palm images are labelled. Typical image samples contained in this dataset is shown below.
ROI: for a given palm image, a palmprint ROI image will be generated. The example ROI samples are shown below.
We have also developed a matlab labeling tool for labeling keypoints on palm images, whose interface is shown in the image below.
This labeling tool and the user instructions can be found here https://github.com/Shelro/MarkToolForPalmprintPoint.
Source Codes
Note: all these codes are implemented in Matlab and run on mac OSX.
1. source code.zip(Code: fc8s)
These codes can fulfill two tasks, generating annotations for keypoint detection and generating palmprint ROIs.
Last update: Feb. 24, 2020