Multisensor Optical and Latent Fingerprint Database

doi:10.1109/ACCESS.2015.2428631

Home
/
Papers
/
Multisensor Optical and Latent Fingerprint Database

Journal Article•DOI•

Multisensor Optical and Latent Fingerprint Database

Anush Sankaran¹, Mayank Vatsa¹, Richa Singh¹•Institutions (1)

Indraprastha Institute of Information Technology¹

30 Apr 2015-IEEE Access (IEEE)-Vol. 3, pp 653-665

TL;DR: This paper presents the multisensor optical and latent fingerprint database of more than 19000 fingerprint images with different intraclass variations during fingerprint capture, and showcases the baseline results of various matching experiments on this database.

read less

Abstract: Large-scale fingerprint recognition involves capturing ridge patterns at different time intervals using various methods, such as live-scan and paper-ink approaches, introducing intraclass variations in the fingerprint. The performance of existing algorithms is significantly affected when fingerprints are captured with diverse acquisition settings such as multisession, multispectral, multiresolution, with slap, and with latent fingerprints. One of the primary challenges in developing a generic and robust fingerprint matching algorithm is the limited availability of large data sets that capture such intraclass diversity. In this paper, we present the multisensor optical and latent fingerprint database of more than 19000 fingerprint images with different intraclass variations during fingerprint capture. We also showcase the baseline results of various matching experiments on this database. The database is aimed to drive research in building robust algorithms toward solving the problem of latent fingerprint matching and handling intraclass variations in fingerprint capture. Some potential applications for this database are identified and the research challenges that can be addressed using this database are also discussed.

...read moreread less

Citations

PDF

Open Access

More filters

Journal Article•DOI•

Impact of digital fingerprint image quality on the fingerprint recognition accuracy

[...]

Mohammad A. Alsmirat¹, Fatima Abdalla Al-Alem¹, Mahmoud Al-Ayyoub¹, Yaser Jararweh¹, Brij B. Gupta² - Show less +1 more•Institutions (2)

Jordan University of Science and Technology¹, National Institute of Technology, Kurukshetra²

01 Feb 2019-Multimedia Tools and Applications

TL;DR: The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.

...read moreread less

Abstract: Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.

...read moreread less

154 citations

Cites background or methods from "Multisensor Optical and Latent Fing..."

...IIIT-D multi-sensor optical and latent fingerprint [49] contains 19200 images acquired from 100 subjects using different sensors....
[...]
...Beside SecuGen Hamster IV, other optical devices were used to collect the IIIT-D Multi-sensor Optical and Latent Fingerprint [49]....
[...]

Journal Article•DOI•

Overview of the combination of biometric matchers

[...]

Alessandra Lumini¹, Loris Nanni²•Institutions (2)

University of Bologna¹, University of Padua²

01 Jan 2017-Information Fusion

TL;DR: Several systems and architectures related to the combination of biometric systems, both unimodal and multimodal, are overviews, classifying them according to a given taxonomy, and a case study for the experimental evaluation of methods for biometric fusion at score level is presented.

...read moreread less

123 citations

Additional excerpts

...MOLF [71]: The IIIT-D Multi-sensor Optical and Latent Fingerprint17 is a database of 19,200 fingerprints collected from 100 subjects using five different capture methods: 3 sensors for live scan and 2 acquisitions of latent fingerprints....
[...]
...Reference Name Year Biometric trait (sensors) Users [68] SCFace 2011 Face (NIR, VIS) 130 [69] CASIA NIR-VIS 2013 Face (NIR, VIS) 725 [70] THID 2014 Hand (NIR, TIR, VIS) 100 [71] MOLF 2015 Fingerprint (optical sensor, latent fingerprint) 100 [72] ND-NIVL 2015 Face (NIR, VIS) 402 Table 3....
[...]
...Reference Name Year Biometric trait (sensors) Users [68] SCFace 2011 Face (NIR, VIS) 130 [69] CASIA NIR-VIS 2013 Face (NIR, VIS) 725 [70] THID 2014 Hand (NIR, TIR, VIS) 100 [71] MOLF 2015 Fingerprint (optical sensor, latent fingerprint) 100 [72] ND-NIVL 2015 Face (NIR, VIS) 402 SCface [68] is a database of static images of human faces taken in uncontrolled indoor environment using five video surveillance cameras of various qualities....
[...]
...MOLF [71]: The IIIT-D Multi-sensor Optical and Latent Fingerprint(17) is a database of 19,200 fingerprints collected from 100 subjects using five different capture methods: 3 sensors for live scan and 2 acquisitions of latent fingerprints....
[...]

Journal Article•DOI•

Group sparse autoencoder

[...]

Anush Sankaran¹, Mayank Vatsa¹, Richa Singh¹, Angshul Majumdar¹•Institutions (1)

Indraprastha Institute of Information Technology¹

01 Apr 2017-Image and Vision Computing

TL;DR: This research considers autoencoder as the feature learning architecture and proposes 2,1-norm based regularization to improve its learning capacity, called as Group Sparse AutoEncoder (GSAE), and formulate the problem of minutia extraction as a two-class classification problem and learn the descriptor using the novel formulation of GSAE.

...read moreread less

50 citations

Cites background from "Multisensor Optical and Latent Fing..."

...NIST MOLF [23] VeriFinger VeriFinger 78....
[...]
...• Perform extensive testing and analysis of the proposed minutiae extractor on two public latent fingerprint databases, namely NIST SD-27 [22] and MOLF [23]....
[...]
...• MOLF dataset [23]: It consists of 4, 400 latent fingerprints from 100 different subjects (all 10 fingers)....
[...]

Journal Article•DOI•

Multi-task CNN for restoring corrupted fingerprint images

[...]

Wei Jing Wong¹, Shang-Hong Lai¹, Shang-Hong Lai²•Institutions (2)

National Tsing Hua University¹, Microsoft²

01 May 2020-Pattern Recognition

TL;DR: Experimental results show significant improvement on both image quality and fingerprint matching accuracy after applying the proposed fingerprint image enhancement technique to several well-known fingerprint datasets.

...read moreread less

40 citations

Journal Article•DOI•

Automated latent fingerprint identification system: A review.

[...]

Nancy Singla¹, Manvjeet Kaur¹, Sanjeev Sofat¹•Institutions (1)

PEC University of Technology¹

24 Feb 2020-Forensic Science International

TL;DR: An extensive review of the work done by eminent researchers in the development of an automated latent fingerprint identification system is provided.

...read moreread less

38 citations

1
2
3
4
…
5
6
7
8
9
10
11
12
13
14

Collapse

References

PDF

Open Access

More filters

Book•

Handbook of Fingerprint Recognition

[...]

Davide Maltoni¹, Dario Maio², Anil K. Jain², Salil Prabhakar¹•Institutions (2)

Michigan State University¹, University of Bologna²

10 Mar 2005

TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.

...read moreread less

Abstract: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

...read moreread less

3,821 citations

Journal Article•DOI•

FVC2000: fingerprint verification competition

[...]

Dario Maio¹, Davide Maltoni¹, Raffaele Cappelli¹, James L. Wayman², Anil K. Jain³ - Show less +1 more•Institutions (3)

University of Bologna¹, San Jose State University², Michigan State University³

01 Mar 2002-IEEE Transactions on Pattern Analysis and Machine Intelligence

TL;DR: This work states that the FVC2000 protocol, databases, and results will be useful to all practitioners in the field not only as a benchmark for improving methods, but also for enabling an unbiased evaluation of algorithms.

...read moreread less

Abstract: Reliable and accurate fingerprint recognition is a challenging pattern recognition problem, requiring algorithms robust in many contexts. FVC2000 competition attempted to establish the first common benchmark, allowing companies and academic institutions to unambiguously compare performance and track improvements in their fingerprint recognition algorithms. Three databases were created using different state-of-the-art sensors and a fourth database was artificially generated; 11 algorithms were extensively tested on the four data sets. We believe that FVC2000 protocol, databases, and results will be useful to all practitioners in the field not only as a benchmark for improving methods, but also for enabling an unbiased evaluation of algorithms.

...read moreread less

815 citations

Additional excerpts

...FVC 2000 [19] 110×4 880×4 ✓ ✓ ✓ Low-cost optical, Low-cost capacitive, optical, and synthetic fingerprint subsets....
[...]

Proceedings Article•DOI•

FVC2002: Second Fingerprint Verification Competition

[...]

Dario Maio¹, Davide Maltoni¹, Raffaele Cappelli¹, James L. Wayman², Anil K. Jain³ - Show less +1 more•Institutions (3)

University of Bologna¹, San Jose State University², Michigan State University³

11 Aug 2002

TL;DR: The FVC 2002 database, the test protocol and the main differences between FVC2000 and FVC2002 are discussed.

...read moreread less

Abstract: Two years after the first edition, a new Fingerprint Verification Competition (FVC2002) was organized by the authors, with the aim of determining the state-of-the-art in this challenging pattern recognition application. The experience and the feedback received from FVC2000 allowed the authors to improve the organization of FVC2002 and to capture the attention of a significantly higher number of academic and commercial organizations (33 algorithms were submitted). This paper discusses the FVC2002 database, the test protocol and the main differences between FVC2000 and FVC2002. The algorithm performance evaluation will be presented at the 16/sup th/ ICPR.

...read moreread less

677 citations

Additional excerpts

...FVC 2002 [20] 110×4 880×4 ✓ ✓ ✓ Optical, capacitive, and synthetic fingerprint subsets....
[...]

Journal Article•DOI•

MCYT baseline corpus: a bimodal biometric database

[...]

Javier Ortega-Garcia, J. Fierrez-Aguilar, D. Simon, Janneth Gonzalez, Marcos Faundez-Zanuy, V. Espinosa, A. Satue, Inma Hernaez¹, Juan J. Igarza¹, Carlos E. Vivaracho², D. Escudero², Q. I. Moro² - Show less +8 more•Institutions (2)

University of the Basque Country¹, University of Valladolid²

01 Dec 2003

TL;DR: The main purpose has been to consider a large scale population, with statistical significance, in a real multimodal procedure, and including several sources of variability that can be found in real environments.

...read moreread less

Abstract: The current need for large multimodal databases to evaluate automatic biometric recognition systems has motivated the development of the MCYT bimodal database. The main purpose has been to consider a large scale population, with statistical significance, in a real multimodal procedure, and including several sources of variability that can be found in real environments. The acquisition process, contents and availability of the single-session baseline corpus are fully described. Some experiments showing consistency of data through the different acquisition sites and assessing data quality are also presented.

...read moreread less

676 citations

Journal Article•DOI•

Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition

[...]

Raffaele Cappelli¹, Matteo Ferrara¹, Davide Maltoni¹•Institutions (1)

University of Bologna¹

01 Dec 2010-IEEE Transactions on Pattern Analysis and Machine Intelligence

TL;DR: The Minutia Cylinder-Code is introduced, a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles and the feasibility of obtaining a very effective fingerprint recognition implementation for light architectures is demonstrated.

...read moreread less

Abstract: In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.

...read moreread less

565 citations

"Multisensor Optical and Latent Fing..." refers background in this paper

...Therefore, MCC descriptors are utilized for establishing baseline results on the latent fingerprint dataset....
[...]
...In literature, we have observed that localMinutiae Cylinder Code (MCC) [37], [38] description for manually marked minutiae provides state-of-the-art results [39]....
[...]
...The following key observations are made: • Experiment IIa exhibits that state-of-the-art MCC descriptor provides very low rank-50 identification accuracy of about 5%-7%, showcasing the challenging nature of latent fingerprints in this database....
[...]
...The results are computed with two different approaches (a) MCC descriptor and (b) Bozorth3 (an open source matcher) available as a part of NBIS....
[...]