Skip to main content
main-content
Top

Hint

Swipe to navigate through the articles of this issue

01-01-2020 | APPLIED PROBLEMS | Issue 1/2020

Pattern Recognition and Image Analysis 1/2020

Thermal Face Recognition under Spatial Variation Conditions

Journal:
Pattern Recognition and Image Analysis > Issue 1/2020
Author:
Naser Zaeri
Important notes
https://static-content.springer.com/image/art%3A10.1134%2FS1054661820010174/MediaObjects/11493_2020_6058_Fig17_HTML.gif
Naser Zaeri is an associate professor with the Department of Information Technology and Computing (ITC) at the Arab Open University (AOU), Kuwait. He has obtained his PhD in Electrical Engineering from University of Surrey, United Kingdom in 2008. He has obtained his M.Sc. and B.Sc. degrees in Electrical Engineering from Kuwait University (Honor List). He served as the Director of Research and Development at the AOU during (2012–2014). He was the Head of ITC Department at the AOU during (2010–2012). Also, he was with College of Engineering and Petroleum – Kuwait University, as a lecturer. He served as a consultant for many authorities and ministries. Dr. Zaeri has participated in and in charge of many projects in different fields of engineering and technology. He has more than 40 different publications in international journals and conferences. Also, he has served as a reviewer for many international reputable journals. His areas of interest are digital image processing, biometrics, pattern classification, and communications systems.

Abstract

This paper proposes a novel method for degraded thermal face recognition using Hu Li moments. The method deals with spatial variations of thermal images resulting from low resolution and changes in head pose. We describe thermal images with a set of scalar quantities that can capture its significant features at component level. Each thermal image is divided into components where the statistical features of these components are combined using a fusion method. The method finds a combination of multiple statistical patterns to produce an integrated result that is enhanced in terms of information content for correct classification. We show that local representations using Hu Li moments provide higher discriminability and offer robustness against variability due to spatial changes. To evaluate the performance of the proposed method, we conduct thorough experiments and detailed analysis on a database consisting of 7500 images of different poses and variable spatial resolutions. This database is generated from an initial one that originally consists of 1500 images, by down-sampling the original images to four different low resolution levels beside the original level. The results show that the proposed method achieves significantly high recognition rates over various conditions resembling practical scenarios.

Please log in to get access to this content

To get access to this content you need the following product:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 69.000 Bücher
  • über 500 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 58.000 Bücher
  • über 300 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 50.000 Bücher
  • über 380 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Maschinenbau + Werkstoffe




Testen Sie jetzt 30 Tage kostenlos.

Literature
About this article

Other articles of this Issue 1/2020

Pattern Recognition and Image Analysis 1/2020 Go to the issue

MATHEMATICAL THEORY OF IMAGES AND SIGNALS REPRESENTING, PROCESSING, ANALYSIS, RECOGNITION, AND UNDERSTANDING

Variance Based External Dictionary for Improved Single Image Super-Resolution

Premium Partner

    Image Credits