Strengthening surf descriptor with discriminant image filter learning: Application to face recognition

Hamdi Bouchech, Sebti Foufou, Mongi Abidi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face recognition in extreme situations is still challenging to researchers. While several algorithms have shown great recognition results in ideal conditions, accuracy decreases when recognition tasks present a high illumination variation. In this paper, we propose to add two components to the recognition system to make the surf descriptor efficient in such extreme situations. First, we learn a discriminant image filter that maximizes the discrimination of surf. Second, the obtained discriminant surf (d-surf) is further strengthened by using multispectral images instead of broad band images. DSURF and multispectral d-surf (MD-SURF) were evaluated against two face databases: the feret database, which served as a benchmark, and the iris-m3 multispectral face database, which presented sun lighted faces. Our algorithms have been evaluated against three state-of-the-art algorithms that are MBLBP, HGPP and LGBPHS. The results validated the superiority of D-SURF over the traditional surf descriptor, while MD-SURF performed best out of all studied algorithms.

Original languageEnglish (US)
Title of host publication2014 26th International Conference on Microelectronics, ICM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-139
Number of pages4
ISBN (Electronic)9781479981533
DOIs
StatePublished - 2014
Event2014 26th International Conference on Microelectronics, ICM 2014 - Doha, Qatar
Duration: Dec 14 2014Dec 17 2014

Publication series

NameProceedings of the International Conference on Microelectronics, ICM
Volume2015-March

Other

Other2014 26th International Conference on Microelectronics, ICM 2014
CountryQatar
CityDoha
Period12/14/1412/17/14

Keywords

  • FERET
  • Face
  • HGPP
  • IRIS-M
  • LGBPHS
  • MBLBP
  • SURF
  • filter
  • illumination
  • multispectral

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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