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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Arwa H. Salih Hamdany
Northern Technical University Mosul
Computer Science & IT

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Earprint recognition using deep learning technique Arwa H. Salih Hamdany; Aseel Thamar Ebrahem; Ahmed M. Alkababji
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 2: April 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i2.16572

Abstract

Earprint has interestingly been considered for recognition systems. It refers to the shape of ear, where each person has a unique shape of earprint. It is a strong biometric pattern and it can effectively be used for authentications. In this paper, an efficient deep learning (DL) model for earprint recognition is designed. This model is named the deep earprint learning (DEL). It is a deep network that carefully designed for segmented and normalized ear patterns. IIT Delhi ear database (IITDED) version 1.0 has been exploited in this study. The best obtaining accuracy of 94% is recorded for the proposed DEL.
Co-Authors Ahmed M. Alkababji Aseel Thamar Ebrahem