This paper introduces the use of Shi-Tomasi algorithm for drowsiness detection by percentage of eye opening estimation. The authors use the method of eye corner detection to increase the accuracy of eye feature detection because eye corners are more stable for tracking. Eye corners have sharp edge information. In the proposed work, the eye corners within the eye ROI are detected, hence, all the good corner features are obtained. The focus will be placed on designing a system that will accurately set percentage of eye closure to monitor the eyes state in real-time. Keywords: Region of Interest, Electroencephalogram, Shi-Tomasi Algorithm, Facial Salient Points, Corner Detection.