SUNARIO MEGAWAN and WULAN SRI LESTARI and APRIYANTO HALIM (2022) DETEKSI NON-SPOOFING WAJAH PADA VIDEO SECARA REAL TIME MENGGUNAKAN FASTER R-CNN. JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH),, 3 (3). pp. 291-299. ISSN 2686-228X
Full text not available from this repository.Abstract
Face non-spoofing detection is an important job used to ensure authentication security by performing an analysis of the captured faces. Face spoofing is the process of fake faces by other people to gain illegal access to the biometric system which can be done by displaying videos or images of someone's face on the monitor screen or using printed images. There are various forms of attacks that can be carried out on the face authentication system in the form of face sketches, face photos, face videos and 3D face masks. Such attacks can occur because photos and videos of faces from users of the facial authentication system are very easy to obtain via the internet or cameras. To solve this problem, in this research proposes a non-spoofing face detection model on video using Faster R-CNN. The results obtained in this study are the Faster R-CNN model that can detect non-spoof and spoof face in real time using the Raspberry Pi as a camera with a frame rate of 1 fps.
Item Type: | Article |
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Divisions: | Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) > Artikel > Fakultas Informatika |
Depositing User: | Rospi Marlena |
Date Deposited: | 29 Jul 2024 03:39 |
Last Modified: | 29 Jul 2024 03:39 |
URI: | https://repository.mikroskil.ac.id/id/eprint/3534 |