Title: Detection of driver's alertness level based on the Viola and Jones method and logistic regression analysis

Authors: Samir Allach; Mohamed Ben Ahmed; Anouar Abdelhakim Boudhir

Addresses: LIST Laboratory, UAE University, FST of Tangier, Tangier, Morocco ' LIST Laboratory, UAE University, FST of Tangier, Tangier, Morocco ' LIST Laboratory, UAE University, FST of Tangier, Tangier, Morocco

Abstract: The analysis of the face elements' state is a crucial step for the driver's alertness level detection. In this article, we propose a driver's assistant system that activates alarms to alert the drowsy and/or tired driver. Our proposed system contains the following steps: firstly, the recognition of the facial elements (eyes, mouth). Secondly, the system determines the states of the mouth and eyes. Finally, it triggers the alarm in the case of the danger. For the extraction and recognition of the face and its elements (eyes, mouth), we use the Viola and Jones method and we also use logistic regression analysis that takes the supplied vector image to determine if the driver is in drowsiness and/or fatigue. The tests performed on the real video sequences, using an Embedded System, provide good results and may function in real time.

Keywords: smart mobility; ITS; drowsiness and fatigue detection; yawning frequency; embedded system.

DOI: 10.1504/IJIE.2019.101135

International Journal of Intelligent Enterprise, 2019 Vol.6 No.2/3/4, pp.356 - 368

Received: 15 Jan 2018
Accepted: 14 Jan 2019
Published online: 24 Jul 2019 *

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