نویسندگان | Marzieh Tafreshi, Ali M. Fotouhi |
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نشریه | Turkish Journal of Electrical Engineering & Computer Sciences |
نوع مقاله | Full Paper |
تاریخ انتشار | Sep 2016 |
رتبه نشریه | ISI |
نوع نشریه | چاپی |
کشور محل چاپ | ترکیه |
نمایه نشریه | ISI |
چکیده مقاله
In this paper, a fast and accurate algorithm is proposed to recognize open and closed eye states. In the proposed algorithm, firstly, a hierarchical preprocessing stage is used to detect eye areas. This stage employs Haar features to detect face area, color and intensity mappings to extract eye candidate areas, and some simple geometrical relations for final decision of the eye regions. In the second stage of algorithm for detecting eye state, a new proposed descriptor based on histogram of local maximum vertical derivative pattern (LMVDP) in eye areas is extracted and applied to support vector machine (SVM) classifier. Proposed descriptor, while having low computational complexity, is well defined to describe eye features and hence can distinguish well between open and closed eyes. Experimental results on test images show that the proposed algorithm can correctly detect the eye state by the ratio of 98.2%, which is higher than other similar algorithms.