Prototype Design of Login Security Using Face Biometrics With the Eigenface Method

Authors

  • sugeng widodo Universitas Mercubuana Yogyakarta

DOI:

https://doi.org/10.26486/jmai.v4i1.102

Keywords:

Keywords: Face Biometrics, Eigenface, Principal Component Analysis (PCA), Real Time, Lux Meter.

Abstract

Login security is a major problem when using a device that is connected in an outside network or internet network. Therefore a data security using face biometrics is performed. Eigenface is a face recognition method based on the Principal Component Analysis (PCA) algorithm. In short the process is that the image is represented in a combined vector which is made into a single matrix. From this single matrix, we will extract a main feature that will distinguish between one face image and another face image. In using the biometric login system this face is the user registering to the system then the user's face will be trained so that the user will be recognized by the system for login purposes. When a user logs in, the user's face data will be processed in real time and matched with the data in the database so that if the data match, the user will successfully log in. The standard face distance from the webcam is 50-60 cm, while the minimum exposure level of the face that can be recognized is 5 lux, and the angle of the face that the system can still recognize is 40 °.

Downloads

Download data is not yet available.

References

Agustina, I., Fauziah, & Gunaryati, A. 2016. Biometrik pola suara dengan jaringan saraf tiruan. JURNAL TEKNIK INFORMATIKA VOL 9 NO. 2, Hal: 140-147, ISSN: 1979-9160.
Andarinny, A. A., Widodo, C. E., & Adi, K. 2017. Perancangan sistem identifikasi biometrik jari tangan menggunakan Laplacian of Gaussian dan ektraksi kontur. Youngster Physics Journal, Hal: 304-314, ISSN: 2302 - 7371.
Apriadi, A., Michrandi, S., & Azmi, F. 2016. Perancangan otentikasi sidik jari pada biometrik payment design of authentication fingerprint for biometric payment. e-Proceeding of Engineering, Hal: 824-830, ISSN : 2355-9365.
Auliannisa, Rizkia Dwi; Suratman, Fiky Yosef; Rizal, Achmad. 2017. Deteksi Katarak Menggunakan Metode Transformasi Hough Berbasis Android. e-Proceeding of Engineering : Vol.4, No.3, Hal: 3310-3319, ISSN: 2355-9365.
Barri, M. W., Lumenta, A. S., & Wowor, A. 2015. Perancangan Aplikasi SMS GATEWAY Untuk Pembuatan Kartu Perpustakaan di Fakultas Teknik Unsrat. E-journal Teknik Elektro dan Komputer, Hal : 23-28, ISSN : 2301-8402.
Firman, A., Wowor, H., & Najoan, X. 2016. Sistem Informasi Perpustakaan Online Berbasis Web. E-journal Teknik Elektro dan Komputer, Hal : 29-36, ISSN : 2301-8402.
Hasmin, E. 2016. Aplikasi rekam kehadiran dengan deteksi wajah menggunakan metode eignface pada kejaksaan tinggi sulawesi selatan. Seminar Nasional Teknologi Informasi dan Multimedia 2016, Hal: 411-416, ISSN: 2302-3805.
Kalyani. 2017. Various Biometric Authentication Techniques: A Review. Journal of Biometrics & Biostatistics, Hal: 1-5, ISSN: 2155-6180.
Kustian, N. 2017. Analisis komponen utama menggunakan metode eigenface terhadap pengenalan citra wajah. jurnal teknologi, Hal : 44-48, ISSN : 2085 – 1669.
Masrani, H., Ilhamsyah, & Ruslianto, I. 2018. Aplikasi pengenalan pola pada huruf tulisan tangan menggunakan jaringan saraf tiruan dengan metode ekstraksi fitur geometri. Jurnal Coding, Sistem Komputer Untan, Hal: 69-78, ISSN: 2338-493X.
Nugroho, E. 2009. Biometrika Mengenal Sistem Identifikasi Masa Depan. Yogyakarta: C.V ANDI OFFSET.
Nugroho, H. 2017. Image Enhancement Pada Screen Capture CCTV Dengan Menggunakan Metode Histogram Ekualisasi. KINETIK, hal: 99-106, ISSN: 2503-2259.
Pamungkas, P. D., & Hariri, F. R. 2016. Pengenalan Citra Tanda Tangan Menggunakan Metode. Citec Journal, Hal: 269-279, ISSN: 2460-4259.
Yahya, & Nur, M. A. 2018. Pengaruh Aplikasi C# dalam Proses Perhitungan Numerik. Jurnal Informatika dan Teknologi, hal: 79 – 87, e-ISSN 2614-8773.

Downloads

Published

2020-04-21