Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model

This paper presents a new biometric score fusion approach in an identification system using the upper integral with respect to Sugeno’s fuzzy measure. First, the proposed method considers each individual matcher as a fuzzy set in order to handle uncertainty and imperfection in matching scores. Then,...

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Main Authors: Khalid Fakhar, Mohamed El Aroussi, Mohamed Nabil Saidi, Driss Aboutajdine
Format: Article
Language:English
Published: MDPI AG 2015-08-01
Series:Information
Subjects:
Online Access:http://www.mdpi.com/2078-2489/6/3/494
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author Khalid Fakhar
Mohamed El Aroussi
Mohamed Nabil Saidi
Driss Aboutajdine
author_facet Khalid Fakhar
Mohamed El Aroussi
Mohamed Nabil Saidi
Driss Aboutajdine
author_sort Khalid Fakhar
collection DOAJ
description This paper presents a new biometric score fusion approach in an identification system using the upper integral with respect to Sugeno’s fuzzy measure. First, the proposed method considers each individual matcher as a fuzzy set in order to handle uncertainty and imperfection in matching scores. Then, the corresponding fuzzy entropy estimates the reliability of the information provided by each biometric matcher. Next, the fuzzy densities are generated based on rank information and training accuracy. Finally, the results are aggregated using the upper fuzzy integral. Experimental results compared with other fusion methods demonstrate the good performance of the proposed approach.
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spelling doaj.art-7959322b1ac84fedb896aee8e70c933f2022-12-22T03:51:23ZengMDPI AGInformation2078-24892015-08-016349450410.3390/info6030494info6030494Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification ModelKhalid Fakhar0Mohamed El Aroussi1Mohamed Nabil Saidi2Driss Aboutajdine3LRIT Research Laboratory (associated unit to CNRST, URAC no. 29), Faculty of Sciences, Mohammed V University, Rabat 10 000, MoroccoLRIT Research Laboratory (associated unit to CNRST, URAC no. 29), Faculty of Sciences, Mohammed V University, Rabat 10 000, MoroccoLRIT Research Laboratory (associated unit to CNRST, URAC no. 29), Faculty of Sciences, Mohammed V University, Rabat 10 000, MoroccoLRIT Research Laboratory (associated unit to CNRST, URAC no. 29), Faculty of Sciences, Mohammed V University, Rabat 10 000, MoroccoThis paper presents a new biometric score fusion approach in an identification system using the upper integral with respect to Sugeno’s fuzzy measure. First, the proposed method considers each individual matcher as a fuzzy set in order to handle uncertainty and imperfection in matching scores. Then, the corresponding fuzzy entropy estimates the reliability of the information provided by each biometric matcher. Next, the fuzzy densities are generated based on rank information and training accuracy. Finally, the results are aggregated using the upper fuzzy integral. Experimental results compared with other fusion methods demonstrate the good performance of the proposed approach.http://www.mdpi.com/2078-2489/6/3/494multibiometricsidentificationscore level fusionfuzzy integralsfuzzy measures
spellingShingle Khalid Fakhar
Mohamed El Aroussi
Mohamed Nabil Saidi
Driss Aboutajdine
Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
Information
multibiometrics
identification
score level fusion
fuzzy integrals
fuzzy measures
title Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
title_full Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
title_fullStr Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
title_full_unstemmed Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
title_short Applying the Upper Integral to the Biometric Score Fusion Problem in the Identification Model
title_sort applying the upper integral to the biometric score fusion problem in the identification model
topic multibiometrics
identification
score level fusion
fuzzy integrals
fuzzy measures
url http://www.mdpi.com/2078-2489/6/3/494
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AT mohamedelaroussi applyingtheupperintegraltothebiometricscorefusionproblemintheidentificationmodel
AT mohamednabilsaidi applyingtheupperintegraltothebiometricscorefusionproblemintheidentificationmodel
AT drissaboutajdine applyingtheupperintegraltothebiometricscorefusionproblemintheidentificationmodel