Nowadays, drowsiness is a serious cause of traffic accidents, a problem of major concern to society. Driver fatigue or sleepiness decreases the driver's reaction time, reduces attention, and affects the quality of decision making which impairs the driving experience. Therefore, in this paper, a drowsiness detection system is designed based on computer vision, using a cascade of classifiers based on Haar-like features. The system is able to detect the face and eyes of the driver and determine the eyes closure or opening, which concludes the drowsiness of the driver. The paper presents the five primary steps involves which are: video acquirement, frame separation, face detection, eyes detection and drowsiness detection.