Interpretation of fingerprint image quality features extracted by self-organizing maps

Ivan Danov; Martin A. Olsen; Christoph Busch

doi:10.1117/12.2050676

29 May 2014 Interpretation of fingerprint image quality features extracted by self-organizing maps

Ivan Danov, Martin A. Olsen, Christoph Busch

Proceedings Volume 9075, Biometric and Surveillance Technology for Human and Activity Identification XI; 907505 (2014) https://doi.org/10.1117/12.2050676
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

Citation Download Citation

Ivan Danov, Martin A. Olsen, and Christoph Busch "Interpretation of fingerprint image quality features extracted by self-organizing maps", Proc. SPIE 9075, Biometric and Surveillance Technology for Human and Activity Identification XI, 907505 (29 May 2014); https://doi.org/10.1117/12.2050676

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
15 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Image quality

Biometrics

Feature extraction

Machine learning

Calibration

Image analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years