Face Recognition Berbasis Raspberry Pi Pada Keamanan Pintu Otomatis

  • Mauludi Manfaluthy Institut Teknologi dan Kesehatan Jakarta
  • Sinka Wilyanti Institut Teknologi dan Kesehatan Jakarta
  • Yunan Lasito Institut Teknologi dan Kesehatan Jakarta
Keywords: Face Recognition, Raspberry Pi, Selonoid Lock

Abstract

The 4.0 industrial revolution, industry trends began to combine automation technology with cyber technology. For this reason, a security system is needed as a response to the growing development of this cyber technology. One of the security solutions in doing authentication is to use a part of the human body, the face. The system can detect face objects as input images from the camera. After the object is detected, the system will do a matching face with the face image contained in the system database. This system is using the application of Computer Vision in the security system. The image will be processed using the Haar Cascade method to detect facial objects contained in the image. The Eigenface method to compare detected faces with faces in the database. Both of these methods will be processed using Raspberry Pi. Three users test the system with different conditions. For users already registered in the database, the door lock will open automatically. The open door security system will reject users that are not stored in the database and send notifications via the Telegram and Whatsapp applications. The average accuracy of face recognition ranges from 80% - 90% with the distance of the camera as far as 0.45 m in a room with good light. Accuracy and response capabilities are greatly influenced by distance, camera specifications, angle, and light intensity

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Author Biographies

Mauludi Manfaluthy, Institut Teknologi dan Kesehatan Jakarta

Fakultas Teknologi dan Ilmu Komputer Jurusan Teknik Elektro

Sinka Wilyanti, Institut Teknologi dan Kesehatan Jakarta

Fakultas Teknologi dan Ilmu Komputer Jurusan Teknik Elektro

Yunan Lasito, Institut Teknologi dan Kesehatan Jakarta

Fakultas Teknologi dan Ilmu Komputer Jurusan Teknik Elektro

Published
2020-01-09
How to Cite
Manfaluthy, M., Wilyanti, S., & Lasito, Y. (2020). Face Recognition Berbasis Raspberry Pi Pada Keamanan Pintu Otomatis. Prosiding Seminar Nasional Teknoka, 4, I133-I140. https://doi.org/10.22236/teknoka.v4i0.4274