Thermal face recognition using local patterns

Gabriel Hermosilla, Gonzalo Farias, Hector Vargas, Francisco Gallardo, Cesar San-Martin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


The aim of this article is to compare the performance of well-known visible recognition methods but using the thermal spectrum. Specifically, the work considers two local-matching based methods for face recognition commonly used in visible spectrum: Local Binary Pattern (LBP) and Local Derivative Pattern (LDP). The methods are evaluated and compared using the UCHThermalFace database, which includes evaluation methodology that considers real-world conditions. The comparative study results shown that, contrary to what happens in the visible spectrum, the LBP method obtains the best results from the thermal face recognition. On the other hand, LDP results show that it is not an appropriate descriptor for face recognition systems in the thermal spectrum.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
EditorsEduardo Bayro-Corrochano, Edwin Hancock
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783319125671
StatePublished - 2014
Event19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 - Puerto Vallarta, Mexico
Duration: 2 Nov 20145 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
CityPuerto Vallarta


  • Face recognition
  • Local Binary Pattern
  • Local Derivative Pattern
  • Thermal face recognition


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