RANCANG BANGUN SISTEM PENGENALAN WAJAH DENGAN METODE PRINCIPAL COMPONENT ANALYSIS

Authors

  • Salamun Salamun Univbersitas Abdurrab Pekanbaru
  • Firman Wazir Universitas Abdurrab

DOI:

https://doi.org/10.36341/rabit.v1i2.25

Keywords:

PCA, Eigenface, Flatvector, Pengenalan Wajah

Abstract

Wajah merupakan salah satu ukuran fisiologis yang paling mudah dan sering digunakan untuk membedakan identitas individu yang satu dengan yang lainnya. Proses pengenalan wajah ini menggunakan informasi mentah dari pixel citra yang dihasilkan melalui camera yang kemudian direpresentasikan dalam metode Principal Components Analysis. Adapun cara kerja metode Principal Components Analysis adalah dengan menghitung dari rata-rata flatvector pixel dari gambar-gambar yang sudah disimpan dalam suatu database, dari rata-rata flatvector tersebut akan didapatkan nila eigenface masing-masing gambar dan kemudian akan dicari nilai eigenface terdekat dari gambar citra wajah yang ingin dikenali. Hasil pengujian menunjukkan tingkat keberhasilan pengenalan wajah secara keseluruhan sebesar 82,27% dengan data wajah sebanyak 130 gambar.

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Author Biography

Salamun Salamun, Univbersitas Abdurrab Pekanbaru

Dosen Tetap Program Studi Teknik Informatika, Fakultas Teknik, dan Staff Puskom Univbersitas Abdurrab Pekanbaru

juga bertanggung jawab publikasi jurnal Rabit

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Published

2016-07-10

How to Cite

[1]
S. Salamun and F. Wazir, “RANCANG BANGUN SISTEM PENGENALAN WAJAH DENGAN METODE PRINCIPAL COMPONENT ANALYSIS”, rabit, vol. 1, no. 2, pp. 61–77, Jul. 2016.

Issue

Vol. 1 No. 2 (2016): Juli 2016

Section

Articles

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