Dual CNN and texture-based face-iris multimodal biometric system via decision-level fusion

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dc.contributor.authorSerifi, Meryem
dc.contributor.authorSerifi, Umit
dc.date.accessioned2025-03-17T12:27:31Z
dc.date.available2025-03-17T12:27:31Z
dc.date.issued2025
dc.departmentTarsus Üniversitesi
dc.description.abstractMultimodal biometric systems integrate multiple biometric traits to enhance recognition accuracy and robustness. This study introduces a novel face-iris multimodal biometric framework combining texture-based and deep learning methods. The system utilizes uniform local binary patterns applied to capture fine-grained texture features. Additionally, a dual convolutional neural network (CNN) model, incorporating AlexNet and an attention mechanism, extracts high-level discriminative features from entire face and iris images. The attention mechanism prioritizes critical regions in feature maps, improving focus on discriminative details while mitigating noise. The key innovation of the system lies in integrating texture-based and CNN-based features, which collectively enable robust feature extraction and classification. Furthermore, the decision-level fusion strategy using the majority voting technique ensures optimal combination of independent decisions from the methods, providing a resilient final classification decision. Experiments conducted on the CASIA-Iris-Distance database demonstrate a recognition performance of 99.53%, significantly outperforming unimodal and state-of-the-art multimodal systems.
dc.identifier.doi10.1007/s11760-025-03873-7
dc.identifier.issn1863-1703
dc.identifier.issn1863-1711
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85218346125
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1007/s11760-025-03873-7
dc.identifier.urihttps://hdl.handle.net/20.500.13099/2301
dc.identifier.volume19
dc.identifier.wosWOS:001420671400007
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer London Ltd
dc.relation.ispartofSignal Image and Video Processing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectMultimodal biometric System
dc.subjectInformation fusion
dc.subjectDecision level fusion
dc.subjectConvolutional neural networks
dc.subjectDual CNN
dc.subjectUniform local binary patterns
dc.titleDual CNN and texture-based face-iris multimodal biometric system via decision-level fusion
dc.typeArticle

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