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Fingerprint synthesis via latent space representation

Version 2 2024-06-04, 02:21
Version 1 2020-01-21, 01:59
conference contribution
posted on 2024-06-04, 02:21 authored by M Attia, MH Attia, J Iskander, K Saleh, D Nahavandi, A Abobakr, M Hossny, S Nahavandi
© 2019 IEEE. Fingerprint recognition and indexing were addressed extensively in the literature. However, the number of the datasets that are used for research and validation is limited. Due to privacy laws and acts in several countries, it is challenging to release finger prints to the public. Consequently, this imposes a challenge on validating these search techniques on larger datasets that can be couple of hundreds of millions. To overcome this limitation, synthetic fingerprints datasets have been introduced as an alternative solution. In this paper we propose a generative model for synthesising fingerprint datasets. In this present work, the synthetic fingerprints are generated from the latent space representation using variational auto encoder. The network is trained to generate random samples that have same distribution as real finger print using latent vectors. By examining the generated synthetic fingerprints images, the ridge patterns were recognisable in most of cases. The unrecognisable synthetic images are reflecting the presence of low quality images in the training samples of the original dataset. Moreover, the extraction of minutiae relies on the quality of the input fingerprint images. In conclusion, the proposed method was able to generate synthetic image that can be further processed to accurately extract the finger minutiae and orientation field.

History

Pagination

1855-1861

Location

Bari, Italy

Start date

2019-10-06

End date

2019-10-09

ISSN

1062-922X

ISBN-13

9781728145693

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics

Event

Systems, Man and Cybernetics. Conference (2019 : Bari, Italy)

Publisher

IEEE

Place of publication

Piscataway, N.J.