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The PLUS Multi-Sensor and Longitudinal Fingerprint Dataset: An Initial Quality and Performance Evaluation

This is "The Multimedia Signal Processing and Security Lab", short WaveLab, website. We are a research group at the Artificial Intelligence and Human Interfaces (AIHI) Department of the University of Salzburg led by Andreas Uhl. Our research is focused on Visual Data Processing and associated security questions. Most of our work is currently concentrated on Biometrics, Media Forensics and Media Security, Medical Image and Video Analysis, and application oriented fundamental research in digital humanities, individualised aquaculture and sustainable wood industry.

The PLUS Multi-Sensor and Longitudinal Fingerprint Dataset: An Initial Quality and Performance Evaluation

In this IEEE Transactions on Biometrics, Behavior, and Identity Science paper "The PLUS Multi-Sensor and Longitudinal Fingerprint Dataset: An Initial Quality and Performance Evaluation" we present a comprehensive fingerprint dataset, which provides a publicly available baseline for further investigations on the aspects of FP aging. In addition to the introduction of the dataset, we also aim at presenting an initial analysis regarding quality and recognition performance under the aspect of longitudinal changes using stateof- the-art quality measures and recognition systems. The obtained recognition results can be downloaded from this site to comply with the principles of reproducible research.

Abstract

In order to assess longitudinal effects in fingerprint biometrics several studies have been carried out in the last decade. Almost all of these investigations focused on non-public forensic fingerprint datasets because there is hardly any publicly available fingerprint database allowing experiments and a corresponding analysis of longitudinal aspects is often infeasible as the contained fingerprint samples are either captured in one session only or with a short time interval of only a few weeks between the sessions. With this work a new fingerprint dataset (108,106 samples) is introduced which can be used for inter-session (longitudinal) as well as inter-sensor fingerprint investigations. A total of ten different capturing devices based on distinct sensing technologies (optical, capacative, thermal, multispectral) is utilized and the imprints of all ten fingers of each of the 50 participating volunteers were acquired at four different time-separated sessions over 2 years. This enables inter-session as well as cross-device evaluations. Additionally, a first quality and recognition performance evaluation deploying several state-of-the-art minutiae based fingerprint recognition schemes and NFIQ 2.0 as quality measure is presented.

Reference

[Kirchgasser21a   ] The PLUS Multi-Sensor and Longitudinal Fingerprint Dataset: An Initial Quality and Performance Evaluation Simon Kirchgasser, Christof Kauba, Andreas Uhl IEEE Transactions on Biometrics, Behavior, and Identity Science 4:1, pp. 43-56, 2022

Data Set

PLUS-MSL-FP Database

The PLUS Multi-Session and Longitudinal Fingerprint Database (PLUS-MSL-FP) is a publically available fingerprint database. It consists of 108106 fingerprint samples from all fingers of up to 59 different subjects captured at four time-separated session with five samples per finger using ten different fingerprint capturing devices. Further information regarding the data set can be found by the following link:

PLUS-MSL-FP Database

Result Files and Settings

Here it is possible to download all recognition results obtained using NIST Biometric Image Software (NBIS), ANSI/ISO SDK developed by Innovatrics and VeriFinger SDK 11.0 developed by Neurotechnology. The EER values are summarised in three Excel files for better readability. Each files contains 19 different sheets representing the evaluation categories considered in the corresponding publication.
Furthermore, the obtained quality values for all 12 considered quality metrics are included in the downloadable .zip file as well.


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