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

by S. A. Shaban*, Hosnia M. M. Ahmed, D. L. Elsheweikh

Department of Computer Science, Faculty of Specific Education, Mansoura University, Egypt

* Corresponding Author: S. A. Shaban. Email: email

Intelligent Automation & Soft Computing 2023, 35(3), 3295-3315. https://doi.org/10.32604/iasc.2023.030237

Abstract

With the rapid spread of the coronavirus epidemic all over the world, educational and other institutions are heading towards digitization. In the era of digitization, identifying educational e-platform users using ear and iris based multimodal biometric systems constitutes an urgent and interesting research topic to preserve enterprise security, particularly with wearing a face mask as a precaution against the new coronavirus epidemic. This 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 pandemic. The proposed system comprises four steps. The first step is image preprocessing, which includes enhancing, segmenting, and extracting the regions of interest. The 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 images. The third step is feature fusion, where the extracted features of the ear and iris images are combined into one sequential fused vector. The fourth step is the matching, which is executed using the City Block Distance (CTB) for student identification. The 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 system achieved higher accuracy than other related systems.

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Cite This Article

APA Style
Shaban, S.A., Ahmed, H.M.M., Elsheweikh, D.L. (2023). A novel fusion system based on iris and ear biometrics for e-exams. Intelligent Automation & Soft Computing, 35(3), 3295-3315. https://doi.org/10.32604/iasc.2023.030237
Vancouver Style
Shaban SA, Ahmed HMM, Elsheweikh DL. A novel fusion system based on iris and ear biometrics for e-exams. Intell Automat Soft Comput . 2023;35(3):3295-3315 https://doi.org/10.32604/iasc.2023.030237
IEEE Style
S. A. Shaban, H. M. M. Ahmed, and D. L. Elsheweikh, “A Novel Fusion System Based on Iris and Ear Biometrics for E-exams,” Intell. Automat. Soft Comput. , vol. 35, no. 3, pp. 3295-3315, 2023. https://doi.org/10.32604/iasc.2023.030237



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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