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"The friction ridge pattern is a 3D structure which, in its natural state, is not deformed by contact with a surface''. Building upon this rather trivial observation, the present work constitutes a first solid step towards a paradigm shift in fingerprint recognition from its very foundations. We explore and evaluate the feasibility to move from current technology operating on 2D images of elastically deformed impressions of the ridge pattern, to a new generation of systems based on full-3D models of the natural nondeformed ridge pattern itself.

Instructions: 

The present data release contains the data of 2 subjects of the 3D-FLARE DB.

 

These data is released as a sample of the complete database as these 2 subjects gave their specific consent for the distribution of their 3D fingerprint samples.

 

The acquisition system and the database are described in the article:

 

[ART1] J. Galbally, L. Beslay and G. Böstrom, "FLARE: A Touchless Full-3D Fingerprint Recognition System Based on Laser Sensing", IEEE ACCESS, vol. 8, pp. 145513-145534, 2020. 

DOI: 10.1109/ACCESS.2020.3014796.

 

We refer the reader to this article for any further details on the data.

 

This sample release contains the next folders:

 

- 1_rawData: it contains the 3D fingerprint samples as they were captured by the sensor describe in [ART1], with no processing. This folder includes the same 3D fingerprints in two different formats:

* MATformat: 3D fingerprints in MATLAB format

* PLYformat: 3D fingerprints in PLY format

 

- 2_processedData: it contains the 3D fingerprint samples after the two initial processing steps carried out before using the samples for recognition purposes. These files are in MATLAB format. This folder includes:

* 2a_Segmented: 3D fingerprints after being segemented according to the process described in Sect. V of [ART1]

* 2b_Detached: 3D fingerprints after being detached according to the process described in Sect. VI of [ART1]

 

The naming convention of the files is as follows: XXXX_AAY_SZZ

XXXX: 4 digit identifier for the user in the database

AA: finger identifier, it can take values: LI (Left Index), LM (Left Middle), RI (Right Index), RM (Right middle)

Y: sample number, with values 0 to 4

ZZ: acquisition speed, it can take values 10, 30 or 50 mm/sec

 

With the data files we also provide a series of example MATLAB scripts to visualise the 3D fingerprints:

readplytomatrix.m

showFilesPLYformat.m

showFilesRaw.m

showFilesSegmented.m

 

We cannot guarantee the correct functioning of these scripts depending on the MATLAB version you are running.

 

Two videos of the 3D fingerprint scanner can be checked at:

https://www.youtube.com/watch?v=XfbumvzXxnU

https://www.youtube.com/watch?v=2U6fqPIWzMg&t

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This dataset is input images for image stitching. The images have various parallax level. So, we grouped the images into five groups according to parallax level.

Some images are from the existing dataset and the other images are added by us.

 

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