Security systems widespread and play essential roles in our lives. The strongest security systems can be built by biometric trails. Earprint can be considered as one of the most important biometrics, especially for phone communications. Here, an earprint database has firstly been established by collecting a big number of earprint images, where an acquisition device is designed and utilized. Preprocessing steps are adopted for segmenting an acquired image and extracting the earprint pattern. Deep Learning (DL) techniques that are currently widely exploited have limited use for individual verifications based on earprint patterns. So, a DL model has been suggested for personal verification in this study. Furthermore, a communication prototype has been designed to analyze an earprint, then, provide a secure mobile phone call.
| Autorius: | Sarah Othman Ali, Raid Rafi Omar Al-Nima, Emad A. Mohammed, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2021 |
| Knygos puslapių skaičius: | 92 |
| ISBN-10: | 6204731831 |
| ISBN-13: | 9786204731834 |
| Formatas: | 220 x 150 x 6 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
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