FACE RECOGNITION SYSTEM FOR HOME SECURITY APPLICATION

A tétel rövid nézete
dc.contributor.advisorVígh, Dániel
dc.contributor.authorAbdalla, Hussein
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-12-12T16:27:35Z
dc.date.available2025-12-12T16:27:35Z
dc.date.created2025-11-30
dc.description.abstractThis thesis presents the design and implementation of a Raspberry Pi 5–based smart lock that uses CNN powered facial recognition with RFID as a fallback method. It explains the theory behind modern face recognition, including detection, alignment, embedding, matching, and software anti-spoofing to defend against printed, screen, and video attacks. The system integrates a camera, servo lock, RFID module, and custom PCB with power management to create a complete embedded hardware platform. A full software pipeline using YuNet, SFace, cosine similarity, and DeepFace liveness detection provides secure user verification. The prototype is also connected to a mobile app via MQTT for remote control and monitoring. Testing shows that the device reliably identifies enrolled users, rejects impostors, and demonstrates that low-cost 2D vision can provide secure home access.
dc.description.courseMechatronical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent60
dc.identifier.urihttps://hdl.handle.net/2437/399846
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectFace Recognition
dc.subjectSmart Lock
dc.subjectHome Security
dc.subjectBiometric Scan
dc.subject.dspaceEngineering Sciences
dc.subject.dspaceInformatics
dc.subject.dspaceEngineering Sciences::Electrical Engineering
dc.titleFACE RECOGNITION SYSTEM FOR HOME SECURITY APPLICATION
dc.title.translatedARCFELISMERŐS RENDSZER OTTHONI BIZTONSÁGI ALKALMAZÁSOKHOZ
Fájlok
Eredeti köteg (ORIGINAL bundle)
Megjelenítve 1 - 1 (Összesen 1)
Nincs kép
Név:
Thesis DEA.pdf
Méret:
1.27 MB
Formátum:
Adobe Portable Document Format
Leírás:
Megjelenítés
Engedélyek köteg
Megjelenítve 1 - 1 (Összesen 1)
Nincs kép
Név:
license.txt
Méret:
1.69 KB
Formátum:
Item-specific license agreed upon to submission
Leírás:
Letöltés
Gyűjtemények
Theses (Department of Electrical Engineering and Mechatronics)