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A Study on an Open/Closed Eye Detection Algorithm for Drowsy Driver Detection
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 Title & Authors
A Study on an Open/Closed Eye Detection Algorithm for Drowsy Driver Detection
Kim, TaeHyeong; Lim, Woong; Sim, Donggyu;
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In this paper, we propose an algorithm for open/closed eye detection based on modified Hausdorff distance. The proposed algorithm consists of two parts, face detection and open/closed eye detection parts. To detect faces in an image, MCT (Modified Census Transform) is employed based on characteristics of the local structure which uses relative pixel values in the area with fixed size. Then, the coordinates of eyes are found and open/closed eyes are detected using MHD (Modified Hausdorff Distance) in the detected face region. Firstly, face detection process creates an MCT image in terms of various face images and extract criteria features by PCA(Principle Component Analysis) on offline. After extraction of criteria features, it detects a face region via the process which compares features newly extracted from the input face image and criteria features by using Euclidean distance. Afterward, the process finds out the coordinates of eyes and detects open/closed eye using template matching based on MHD in each eye region. In performance evaluation, the proposed algorithm achieved 94.04% accuracy in average for open/closed eye detection in terms of test video sequences of gray scale with 30FPS/ resolution.
PCA;Hausdorff distance;Eye detection;Drowsy driver detection;Distance transform;
 Cited by
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