Anshul Mahajan^*, Sunil K. Singla

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1623-1649, 2024, DOI:10.32604/cmes.2024.054468 - 27 September 2024

Abstract The identification of individuals through ear images is a prominent area of study in the biometric sector. Facial recognition systems have faced challenges during the COVID-19 pandemic due to mask-wearing, prompting the exploration of supplementary biometric measures such as ear biometrics. The research proposes a Deep Learning (DL) framework, termed DeepBio, using ear biometrics for human identification. It employs two DL models and five datasets, including IIT Delhi (IITD-I and IITD-II), annotated web images (AWI), mathematical analysis of images (AMI), and EARVN1. Data augmentation techniques such as flipping, translation, and Gaussian noise are applied to More >

Ghoroub Talal Bostaji^*, Emad Sami Jaha

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1571-1591, 2023, DOI:10.32604/csse.2023.039701 - 28 July 2023

Abstract Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues. Therefore, biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics. Among different viable biometric modalities, the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems. In recent years, most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results. Nevertheless, such traditional models can… More >

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

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3295-3315, 2023, DOI:10.32604/iasc.2023.030237 - 17 August 2022

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… More >