Deteksi Mata dan Alis Menggunakan AdaBoost Classifier dan Haar Cascade
DOI:
https://doi.org/10.37859/jf.v14i3.7394
Abstract
Pada saat pandemi COVID-19 menggunakan masker merupakan kebutuhan sehari – hari. Penggunaan masker secara masif menimbulkan tantangan pada pengenalan wajah, kamera pengawas, estimasi usia, sistem pelacakan tatapan mata, dan sistem monitoring kelelahan driver yang berbasis deteksi wajah. Dari permasalahan tersebut maka dibutuhkan sebuah penelitian untuk dapat mendeteksi mata dan alis pada wajah yang menggunakan masker. Penelitian ini bertujuan untuk mengimplementasikan deteksi mata dan alis menggunakan metode Haar Cascade. Beberapa proses Haar Cascade yang dilakukan diantaranya Preprocessing, Integral Image, Adaboost, dan Cascade. Hasil penelitian menunjukkan metode Haar Cascade berhasil dalam mendeteksi objek mata dan alis dengan cukup baik dengan tingkat akurasi 95% pada data wajah bermasker, 90% pada wajah berkacamata, 87% pada wajah berkacamata dan miring, 87% pada wajah berkacamata, miring dan mata tertutup
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