Abstract: A cost-effective and robust method for localizing and tracking drowsiness state of the eyes of driver by using images captured by near infrared (IR) camera disposed on the vehicle, the said method comprising the processor implemented steps of: Real-time tracking of the face and localizing eye bounding box within the face bounding box in the captured image by comparing the gray values with threshold using the segmentation process; tracking the eyes by computing the centroid of the eye, target model histogram and target candidate model histogram for one location to another by comparing them to identify distance and calculating the displacement of the target center by the weighted means, wherein the target model histogram and target candidate model histogram are computed based on the feature space; and detecting the drowsiness state of the eyes using histogram equalization, Morphological operations and texture based parameters using histogram and grey level co-occurrence matrices.

Abstract: A cost-effective and robust method for localizing and tracking drowsiness state of the eyes of driver by using images captured by near infrared (IR) camera disposed on the vehicle, the said method comprising the processor implemented steps of: Real-time tracking of the face and localizing eye bounding box within the face bounding box in the captured image by comparing the gray values with threshold using the segmentation process; tracking the eyes by computing the centroid of the eye, target model histogram and target candidate model histogram for one location to another by comparing them to identify distance and calculating the displacement of the target centre by the weighted means, wherein the target model histogram and target candidate model histogram are computed based on the feature space; and detecting the drowsiness state of the eyes using histogram equalization, Morphological operations and texture based parameters using histogram and grey level co-occurrence matrices.