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A Novel Fusion system Based on Iris and Ear Biometrics for E-exams

Intelligent Automation & soft Computing 2023年第3期35卷 3295-3315页

作者： s.A.shaban Hosnia M.M.Ahmed D.L.Elsheweikh Department of Computer science Faculty of Specific EducationMansoura UniversityEgypt

With the rapid spread of the coronavirus epidemic all over the world,educational and other institutions are heading towards *** the era of digitization,identifying educational e-platform users using ear and iris based multi-modal biometric systems constitutes an urgent and interesting research topic to pre-serve enterprise security,particularly with wearing a face mask as a precaution against the new coronavirus *** study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations(E-exams)during the COVID-19 *** proposed system comprises four ***ﬁrst step is image preprocessing,which includes enhancing,segmenting,and extracting the regions of *** second step is feature extraction,where the Haralick texture and shape methods are used to extract the features of ear images,whereas Tamura texture and color histogram methods are used to extract the features of iris *** third step is feature fusion,where the extracted features of the ear and iris images are combined into one sequential fused *** fourth step is the matching,which is executed using the City Block Dis-tance(CTB)for student identiﬁ***ﬁndings of the study indicate that the system’s recognition accuracy is 97%,with a 2%False Acceptance Rate(FAR),a 4%False Rejection Rate(FRR),a 94%Correct Recognition Rate(CRR),and a 96%Genuine Acceptance Rate(GAR).In addition,the proposed recognition sys-tem achieved higher accuracy than other related systems.

关键词： City block distance(CTB) Covid-19 ear biometric e-exams feature-level fusion iris biometric multimodal biometric student’s identity

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