Optimalisasi Deteksi Wajah Real-Time Menggunakan HAAR Cascade Classifier berbasis OpenCV

Alfan Rizaldy Pratama; Muhammad Nasrudin; Andri Faudzan Adziima; Shindi Shella May Wara

doi:10.26905/jasiek.v7i1.15485

Authors

Alfan Rizaldy Pratama Universitas Pembangunan Nasional Veteran Jawa Timur https://orcid.org/0009-0006-7852-6346
Muhammad Nasrudin Universitas Pembangunan Nasional Veteran Jawa Timur
Andri Faudzan Adziima Universitas Pembangunan Nasional Veteran Jawa Timur
Shindi Shella May Wara Universitas Pembangunan Nasional Veteran Jawa Timur

DOI:

https://doi.org/10.26905/jasiek.v7i1.15485

Keywords:

Color Palette, Face detection, FPS performance improvement, HAAR Cascade Classifier, Real-time

Abstract

Nowadays, the face is one of the features that is widely used in various aspects of life such as security which includes access control and surveillance, biometrics which includes attendance systems, and many others. The obstacles found in implementing this are generally about speed performance when detecting, this is vital because if the process takes a long time, misconceptions and system errors will occur. HAAR Cascade Classifier is one of the most widely used lightweight face detection algorithms. In this research, by analyzing the use of grayscale color compared to RGB, a performance increase of 6.17% is obtained with an average FPS on RGB of 25.63 while on grayscale it is 27.21.

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