Pengenalan Ekspresi Wajah Pengemudi Berbasis Fitur Eigenface dan Gray Level Co-Occurance Matrice

Authors

  • Sudirman S. Panna Universitas Ichsan Gorontalo
  • Aprianto Alhamad Universitas Ichsan Gorontalo
  • Kartika Chandra Pelangi Universitas Ichsan Gorontalo

DOI:

https://doi.org/10.26418/jp.v9i2.61857

Keywords:

FER, Fatique Detection, Eigenface, GLCM, ANN

Abstract

Umumnya kecelakaan lalu lintas disebabkan oleh terjadinya penurunan konsentrasi saat berkendara yang diakibatkan oleh rasa kantuk yang dialami, terdapat 20% kecelakaan disebabkan oleh penurunan konsentrasi. Teknologi computer vision berupaya mengembangkan teknologi driving assistance dalam menyelesaikan persoalan kecelakaan lalu lintas. Penelitian sebelumnya terkait deteksi ekspresi wajah pengemudi menyimpulkan bahwa metode eigenface memiliki waktu komputasi yang cukup baik akan tetapi hanya mampu menghasilkan akurasi sebesar 80%, sehingganya dalam penelitian ini akan dilakukan pengabungan dua buah fitur ekstraksi (eigenface dan GLCM) serta algoritma ANN sebagai pengklasifikasi. Pada penelitian yang kami lakukan menunjukkan metode yang diusulkan dapat memberikan performa dengan nilai akurasi sebesar 83%, recall sebesar 86%, precission sebesar 81% dan F1-Score sebesar 83%.

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Published

2023-08-24