Real-Time Driver Drowsiness Detection System Based on PERCLOS and Grayscale Image Processing

2016 ◽  
Author(s):  
Jun-Juh Yan ◽  
Hang-Hong Kuo ◽  
Ying-Fan Lin ◽  
Teh-Lu Liao
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Detection System ◽  
Grayscale Image ◽  
Drowsiness Detection ◽  
Driver Drowsiness

scholarly journals Driver Drowsiness Detection System using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 2270-2272
Author(s):  
Charan M
Keyword(s):  
Real Time ◽  
Web Application ◽  
Detection System ◽  
Smart Phone ◽  
Learning Approaches ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
The Face ◽  
Bounding Boxes ◽  
Traditional Image

We propose a Driver drowsiness detection system, the purposes of which are to prevent from dangerous cause and to avoid accidents. Since all the processes on image recognition performed on a smart phone, the system does not need to send images to a server and runs on an android smart phone in a real-time way. Automatic image-based recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches without human supervision real-time drowsiness detection. This model classifies whether the person’s eyes are opened or closed. To recognize the face, a user should have to adjust camera such a way that it covers his face first, and then the system starts recognition within the indicated bounding boxes. In addition, the system estimates the actions of the person. This recognition process is performed repeatedly about every second. We will implement this system as Web application effectively for real-time recognition.

Visual-based Real Time Driver Drowsiness Detection System Using CNN

2021 ◽  
Author(s):  
Jonathan Flores-Monroy ◽  
Mariko Nakano-Miyatake ◽  
Gabriel Sanchez-Perez ◽  
Hector Perez-Meana
Keyword(s):  
Real Time ◽  
Detection System ◽  
Drowsiness Detection ◽  
Driver Drowsiness

scholarly journals Driver Drowsiness Detection using MATLAB

2019 ◽  
Vol 8 (2) ◽  
pp. 843-844
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Binary Image ◽  
Detection Function ◽  
Image Processing Techniques ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
Face Features ◽  
Processing Techniques

Drowsiness is major cause of accidents. So, this drowsiness detection system alerts the drowsy drivers in order to reduce the risk of potential accidents. The proposed system uses computer vision and image processing technology of MATLAB for detecting the drowsiness. MATLAB detects if eyes are closed or open using various image processing techniques performed using Viola-Jones face features detecting algorithm and skin y,cb,cr values detection function ,converting image into a binary image which was further employed to extract eye characteristics, and its closing frequency, determining drowsiness.

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