Novel image fusion scheme based on maximum ratio combining for robust multispectral face recognition

Faten Omri, Sebti Foufou

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

Abstract

Recently, the research in multispectral face recognition has focused on developing efficient frameworks for improving face recognition performance at close-up distances. However, few studies have investigated the multispectral face images captured at long distance. In fact, great challenges still exist in recognizing human face in images captured at long distance as the image quality might be affected and some important features masked. Therefore, multispectral face recognition tools and algorithms should evolve from close-up distances to long distances. To address these issues, we present in this paper a novel image fusion scheme based on Maximum Ratio Combining algorithm and improve multispectral face recognition at long distance. The proposed method is compared with similar super-resolution method based on the Maximum likelihood algorithm. Simulation results show the efficiency of the proposed approach in term of average variance of detection error.

Original languageEnglish (US)
Title of host publicationTwelfth International Conference on Quality Control by Artificial Vision
EditorsFabrice Meriaudeau, Olivier Aubreton
PublisherSPIE
ISBN (Electronic)9781628416992
DOIs
StatePublished - 2015
Event12th International Conference on Quality Control by Artificial Vision - Le Creusot, France
Duration: Jun 3 2015Jun 5 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9534
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other12th International Conference on Quality Control by Artificial Vision
Country/TerritoryFrance
CityLe Creusot
Period6/3/156/5/15

Keywords

  • Maximum Ratio Combining
  • Maximum likelihood algorithm
  • Multispectral face recognition
  • image fusion

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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