Edge based eye-blink detection for computer vision syndrome

Abstract

Living in an information age the whole earth is a small globe in our hands with the advancements of computers, smartphones etc. The usage of computers in our day-to-day activities has increased enormously leading to both positive and negative effects in our lives. The negative effects are related to health problems such as Computer Vision Syndrome (CVS) etc. Prolonged use of computers would lead to a significant reduction of spontaneous eye blink rate due to the high visual demand of the screen and concentration on the work. The proposed system develops a prototype using blink as a solution to prevent CVS. The first part of the work captures video frames using web-camera mounted on the computer or laptop. These frames are processed dynamically by cropping only the eyes. The algorithms performed on the eye-frames are direct pixel count, gradient. Canny edge and Laplacian of Gaussian (LoG). These determine the eye-status based on the threshold value and the proposed idea, the difference between upper and lower eye frames. Various experiments are done and their algorithms are compared and concluded that the proposed algorithm yields 99.95% accuracy.