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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

Levels of fusion in multimodal biometric systems.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig2: Levels of fusion in multimodal biometric systems.

Mentions: (5) Score Level. It refers to the combination of matching scores provided by the different systems. The score level fusion techniques are divided into two main sets: fixed rules (AND, OR, majority, maximum, minimum, sum, product and arithmetic rules) and trained rules (weighted sum, weighted product, fisher linear discriminate, quadratic discriminate, logistic regression, support vector machine, multilayer perceptrons, and Bayesian classifier ) [22]. Figure 2 shows the five levels of biometric fusion.


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

Benaliouche H, Touahria M - ScientificWorldJournal (2014)

Levels of fusion in multimodal biometric systems.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig2: Levels of fusion in multimodal biometric systems.
Mentions: (5) Score Level. It refers to the combination of matching scores provided by the different systems. The score level fusion techniques are divided into two main sets: fixed rules (AND, OR, majority, maximum, minimum, sum, product and arithmetic rules) and trained rules (weighted sum, weighted product, fisher linear discriminate, quadratic discriminate, logistic regression, support vector machine, multilayer perceptrons, and Bayesian classifier ) [22]. Figure 2 shows the five levels of biometric fusion.

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