This repository consists of the contactless fingerprint acquisition app used to acquire the RidgeBase Dataset
The repository consists of a front-end application built using React Expo and back-end built on python flask. The front-end sends the acquired image to the backend for storage and no image is store on the local device. Details of the app can be found in this WIFS 2021 paper.
- Clone the repository
- Start the client app:
cd client
npm start or expo start- Start the server app:
cd server
python3 api.py- Insert the server address endpoint in the client code:
App.tsx - Generate a id mapping file comma separated and replace it with mapping.csv in server folder.
If you use RidgeBase dataset or this associated app in your research please cite following papers:
Plain Text:
B. Jawade, D. Mohan, S. Setlur, N. Ratha and V. Govindaraju "RidgeBase: A Cross-Sensor Multi-Finger Contactless Fingerprint Dataset," 2022 IEEE International Joint Conference on Biometrics (IJCB), 2022
`
@book{jawade2022ridgebase,
author = "B. Jawade and D. Mohan and S. Setlur and N. Ratha and V. Govindaraju",
title = "RidgeBase: A Cross-Sensor Multi-Finger Contactless Fingerprint Dataset",
publisher = "2022 {IEEE} International Joint Conference on Biometrics ({IJCB})",
year = 2022
}
Plain Text:
B. Jawade, A. Agarwal, S. Setlur and N. Ratha, "Multi Loss Fusion For Matching Smartphone Captured Contactless Finger Images," 2021 IEEE International Workshop on Information Forensics and Security (WIFS), 2021, pp. 1-6, doi:10.1109/WIFS53200.2021.9648393.
@INPROCEEDINGS{9648393,
author={Jawade, Bhavin and Agarwal, Akshay and Setlur, Srirangaraj and Ratha, Nalini},
booktitle={2021 IEEE International Workshop on Information Forensics and Security (WIFS)},
title={Multi Loss Fusion For Matching Smartphone Captured Contactless Finger Images},
year={2021},
volume={},
number={},
pages={1-6},
doi={10.1109/WIFS53200.2021.9648393}}