Two Unconstrained Biometric Databases

In the last few years the research community has witnessed significant progress in biometric technology, due to the availability of a wide variety of databases. However, the available databases that are currently available present significant setbacks in terms of restricted access to data, low-resolution and restrictions imposed on individuals during the acquisition phase. In this paper, two new public databases are described that have been created, with fingerprint and palm print images and their characteristics are compared with other databases available in the research community. The advantages of these databases are the great variety of individual characteristics, they have no restrictions during acquisition and they have manual ground truth annotation. They were presented in two different international competitions and have been used in research by different authors.

[1]  David Zhang,et al.  A survey of palmprint recognition , 2009, Pattern Recognit..

[2]  Filipe Magalhães,et al.  Hand-Geometry Based Recognition System - A Non Restricted Acquisition Approach , 2012, ICIAR.

[3]  Pengcheng Shi,et al.  Peg-Free Hand Geometry Recognition Using Hierarchical Geomrtry and Shape Matching , 2002, MVA.

[4]  Jie Zhou,et al.  A novel model for orientation field of fingerprints , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[5]  G. Aguilar,et al.  Fingerprint Recognition , 2007, Second International Conference on Internet Monitoring and Protection (ICIMP 2007).

[6]  Adnan Amin,et al.  Fingerprint classification: a review , 2004, Pattern Analysis and Applications.

[7]  Mohamed S. Kamel,et al.  Image Analysis and Recognition , 2014, Lecture Notes in Computer Science.

[8]  Anil K. Jain,et al.  On-line fingerprint verification , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[9]  Gonzalo Bailador,et al.  Invariant Hand Biometrics Feature Extraction , 2011, CCBR.

[10]  Anil K. Jain,et al.  Fingerprint classification , 1996, Pattern Recognit..

[11]  Javier Guerra-Casanova,et al.  Unconstrained and Contactless Hand Geometry Biometrics , 2011, Sensors.

[12]  Aurélio J. C. Campilho,et al.  A new method for the detection of singular points in fingerprint images , 2009, 2009 Workshop on Applications of Computer Vision (WACV).

[13]  V. S. Srinivasan,et al.  Detection of singular points in fingerprint images , 1992, Pattern Recognit..

[14]  Leonid Mestetskiy,et al.  Hand Geometry Analysis by Continuous Skeletons , 2011, ICIAR.

[15]  Edward Richard Henry,et al.  Classification and uses of finger prints , 1928 .

[16]  Jugurta R. Montalvão Filho,et al.  Robust hand image processing for biometric application , 2010, Pattern Analysis and Applications.

[17]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[18]  R. Ostrovsky,et al.  Fingerprint Recognition , 2008 .

[19]  Sharath Pankanti,et al.  On the Individuality of Fingerprints , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Boris Bratnina.  AKADEMSKO PISANJE U DRUŠTVENIM NAUKAMA , 2011 .

[21]  Davide Maltoni,et al.  Fingerprint verification competition 2006 , 2007 .

[22]  Anil K. Jain,et al.  Is there any texture in the image? , 1996, Pattern Recognit..