Abstract
Fatigue driving is one of main problems threatening driving safety. Therefore, it attracts numerous researchers interests. This paper introduces a new method based on eye feature to research the fatigue driving. Firstly, the face is detected by the model of skin-color in the YCbCr color space, which extracted face region from complex background quickly and accurately. Secondly, eye detection includes extracting eye region and detecting eye two steps. Specifically, the proposed method extracts eye region in face image based on gray-scale projection and then detect eye using Hough transform. Finally, calculate the area of the eye profile after dilation and use it as the parameter to analysis eye state. Put forward the standard to recognize fatigue base on the PERCLOS. The experiment results illustrate the efficiency and accurately of the proposed method, especially, detected face as well as extracted eye region with a high accuracy.
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Acknowledgments
This work is supported by the Basic Research Program (Natural Science Foundation) of Jiangsu Province of China (No.BK20130209), the Fundamental Research Funds for the Central Universities (No.2013QNA24), the Project Funded by China Postdoctoral Science Foundation (No.2014M560460), the Project Funded by Jiangsu Postdoctoral Science Foundation (No.1302037C).
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Xu, X., Cui, X., Wang, G., Sun, T., Feng, H. (2015). A New Method for Driver Fatigue Detection Based on Eye State. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham. https://doi.org/10.1007/978-3-319-25754-9_45
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DOI: https://doi.org/10.1007/978-3-319-25754-9_45
Publisher Name: Springer, Cham
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