• DocumentCode
    2234576
  • Title

    Novel biometric features fusion method based on possibility theory

  • Author

    Guesmi, Hanene ; Trichili, Hanene ; Alimi, Adel M. ; Solaiman, Basel

  • Author_Institution
    REGIM: REsearch Groups on Intelligent Machines, National engineering School of Sfax (Tunisia)
  • fYear
    2015
  • fDate
    6-8 July 2015
  • Firstpage
    418
  • Lastpage
    425
  • Abstract
    In this paper, we propose a novel biometric modalities fusion method based on possibility theory. We have integrated this method in a bimodal biometric system. This biometric system is based on the fingerprint and the iris modalities to identify a person. The process of this method consists of two main phases: the features selection phase, and the fusion phase. In the first phase, we select the most relevant features by a proposed selection method based on the genetic algorithm and the possibility theory. Then, in the second phase, the selected features of different biometric modalities are fused by the novel proposed fusion method based on the possibility theory. An experimental evaluation of the bimodal biometric system which used the proposed fusion method shows the good performance of the possibility reasoning in the biometric features fusion
  • Keywords
    Active contours; Biological system modeling; Databases; Feature extraction; Fingerprint recognition; Image segmentation; Phase locked loops; bimodal biometric system; features level; fingerprint; fusion method; iris; person identification; possibility theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics & Cognitive Computing (ICCI*CC), 2015 IEEE 14th International Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    978-1-4673-7289-3
  • Type

    conf

  • DOI
    10.1109/ICCI-CC.2015.7259419
  • Filename
    7259419