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Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

Benaliouche H, Touahria M - ScientificWorldJournal (2014)

Bottom Line: The scores combination approach is used after normalization of both scores using the min-max rule.Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature.The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

View Article: PubMed Central - PubMed

Affiliation: Computer Science Department, University of Ferhat Abbas Sétif 1, Pôle 2 - El Bez, 19000 Sétif, Algeria.

ABSTRACT
This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

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Related in: MedlinePlus

GUI of the identification process in the iris monomodal recognition system.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig8: GUI of the identification process in the iris monomodal recognition system.

Mentions: Both verification and identification processes are implemented. Figures below present the graphical user interfaces GUIs allowing the user to load an iris image from a database and to do segmentation, feature extraction, and either verification (see Figure 7) (the user has to upload another iris image) or identification (see Figure 8) (the system searches similar code in database).


Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

Benaliouche H, Touahria M - ScientificWorldJournal (2014)

GUI of the identification process in the iris monomodal recognition system.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3926359&req=5

fig8: GUI of the identification process in the iris monomodal recognition system.
Mentions: Both verification and identification processes are implemented. Figures below present the graphical user interfaces GUIs allowing the user to load an iris image from a database and to do segmentation, feature extraction, and either verification (see Figure 7) (the user has to upload another iris image) or identification (see Figure 8) (the system searches similar code in database).

Bottom Line: The scores combination approach is used after normalization of both scores using the min-max rule.Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature.The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

View Article: PubMed Central - PubMed

Affiliation: Computer Science Department, University of Ferhat Abbas Sétif 1, Pôle 2 - El Bez, 19000 Sétif, Algeria.

ABSTRACT
This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

Show MeSH
Related in: MedlinePlus