The study focuses on the improvement of the accuracy of the recognition of drowsiness by taking in consideration the constraints of the previous studies. These constraints include obstruction in the eyes, and in the mouth of the driver. The said constraints could be a hinder in the process of detecting the eyes, and the mouth that could affect the process of recognizing drowsiness. The researchers made used of Viola-Jones Algorithm for the detection of the features; face, eyes, and mouth, needed in the developed system to recognize drowsiness. The study proved that the developed system was highly accurate with 91.10%. While the said system without the head movement recognition only got 86.50%. Using t-test formula, it was concluded that there is a significant difference between the accuracy of the system and the existing system without the head movement recognition in recognizing drowsiness of drivers.
Volume 12 | 06-Special Issue
Pages: 315-321
DOI: 10.5373/JARDCS/V12SP6/SP20201037