The Effectiveness Of OpenCV Based Face Detection In Low-Light Environments

Abstract

A face detection experiment based on OpenCV is a technology used to identify and find human faces in digital images or videos. This technology uses algorithms and image processing techniques to analyze the pixels in an image or video frame and determine if they contain a human face. The aim of this research is to determine the effectiveness of OpenCV-based face detection using the Viola-Jones algorithm with low-intensity brightness environmental conditions. The research was conducted with light intensity levels of 10 Lux, 30 Lux, and 50 Lux and was carried out using the camera on the ASUS TUF DASH 15 FX517ZC laptop. Data in evaluation using evaluation metrics containing the formula recall, precision, F-Score, and accuracy. The results of the study showed that experiments with higher light intensities up to 50 Lux showed the best level of efficiency according to the accuracy values (99.2%), f-score(0.996), and recall (0.993), so the system is best done with a brightness of 50 Lux. Face detection is affected by the camera that used, in addition, rotation of face is important for the system to detect faces, despite video recording in high light intensity environments