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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro REKAYASA Pendas : Jurnah Ilmiah Pendidikan Dasar Elektrika Tibuana : Journal of Applied Industrial Engineering Jurnal Teknik Elektro dan Komputer TRIAC Energy : Jurnal Ilmiah Ilmu-Ilmu Teknik Jambura Journal of Electrical and Electronics Engineering Journal of Robotics and Control (JRC) PUBLIKASI PENELITIAN TERAPAN DAN KEBIJAKAN J-Eltrik JTEIN: Jurnal Teknik Elektro Indonesia JASEE Journal of Application and Science on Electrical Engineering SinarFe7 Komparatif: Jurnal Perbandingan Hukum dan Pemikiran Islam Nucleus Journal Jurnal FORTECH
Ubaidillah, Achmad
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Liveness Detection-Based Home Door Security System for Anti-Spoofing Using Intel RealSense F455 Camera and LBPH saputro, Adi kurniawan; Ubaidillah, Achmad; Diputra, Hamzah Arifianto; Laksono, Deni Tri; Ibadillah, Achmad Fiqhi; Nur, Achmad Zain
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 1 (2026): Januari - Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i1.34918

Abstract

Spoofing attacks on facial recognition-based security systems are increasing along with the development of smart home technology. To address this issue, this study proposes a home door security system with the implementation of liveness detection-based anti-spoofing technology using an Intel RealSense F455 camera. The system is designed to verify the authenticity of a user's face in real-time by combining facial texture analysis and the user's physiological responses. The facial detection process is carried out using the Haarcascade algorithm to extract a 160×160 pixel facial area, while facial recognition uses the Local Binary Pattern Histogram (LBPH) method which is relatively stable to variations in lighting and viewing angles. The liveness detection mechanism is implemented mechanically by utilizing the Haarcascade Eye to detect the user's eye movements as an indicator of the presence of a live face, so that the system is able to distinguish real faces from fake media in the form of static photos. The system is integrated with a Telegram bot for real-time access monitoring, where automatic notifications are sent every time a door access attempt occurs. Test results show a facial recognition accuracy rate of 98.93%, with the system successfully detecting and verifying 30 registered users and producing an average confidence value consistently above 80%. Furthermore, the liveness detection mechanism proved effective in preventing photo-based spoofing attacks, with a stable detection success rate throughout the testing. These findings suggest that the integration of LBPH and eye-based liveness detection can improve the reliability of facial recognition-based door security systems.
Co-Authors Achmad Fiqhi Ibadillah Adi Kurniawan Saputro Afif, Nasrul Aliyulhaq, Mohammad Aqiel Muhammad, Dlobith Choirony, Iklil Vurqon Daman Huri Defriyanti, Wenni Tania Dharu Wahyu Pambudi, Achmad Tirta Dian Neipa Purnamasari Diana Rahmawati Dinar Lestari, Adhinda Diputra, Hamzah Arifianto Efriandi, Efriandi Fahmi, Monika Faswia Fajar Sidik, Rahmad Faswia Fahmi, Monika Ghifari, Muhammad Iqbal Akbar Handoko, Kiki Hardiansyah, Muttaqin Hardiwansyah, Muttaqin Hariyanto, Mohammad Slamed Haryanto Haryanto Iyabu, Sissy Rahmatia Juairiyah, Oktaf Karna Wicitra, Adi Kholida, S Ida Khotibul Umam Koko Joni Kurniawan S., Adi Kurniawan Saputro, Adi Lailatul Riski, Ulfa Laksono, Deni Tri Mahmudi, Muhammad Imam Miftachul Ulum, Miftachul Neipa P., Dian Ningrum, Eliya Kristina Nizhomy, Adeb Nur, Achmad Zain pradipta, Hanif Riza Alfita S. Ida Kholida Sakur, Sakur Sari, Indah Apriliana Setya Budi, Tri Sholeh Abdullah, Wahyu Sondang Sumbawati, Meini Sukri, Hanifudin Wahyuni, Ardian Yani, Achmat Yulianto, Achmad