Toward hyperspectral face recognition

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

32 Scopus citations


Face recognition continues to meet significant challenges in reaching accurate results and still remains one of the activities where humans outperform technology. An attractive approach in improving face identification is provided by the fusion of multiple imaging sources such as visible and infrared images. Hyperspectral data, i.e. images collected over hundreds of narrow contiguous light spectrum intervals constitute a natural choice for expanding face recognition image fusion, especially since it may provide information beyond the normal visible range, thus exceeding the normal human sensing. In this paper we investigate the efficiency of hyperspectral face recognition through an in house experiment that collected data in over 120 bands within the visible and near infrared range. The imagery was produced using an off the shelf sensor in both indoors and outdoors with the subjects being photographed from various angles. Further processing included spectra collection and feature extraction. Human matching performance based on spectral properties is discussed.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging -Image Processing
Subtitle of host publicationAlgorithms and Systems VI
StatePublished - 2008
EventImage Processing: Algorithms and Systems VI - San Jose, CA, United States
Duration: 28 Jan 200829 Jan 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherImage Processing: Algorithms and Systems VI
Country/TerritoryUnited States
CitySan Jose, CA


  • Face recognition
  • Hyperspectral imagery
  • Spectral matching


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