ACCIDENT PREVENTION USING EYE DROWSINESS AND YAWNING DETECTION

Mr. Vedant Thube
Datta Megha College of Engineering
Airoli, Navi Mumbai
Mumbai, Maharashtra

Neha Thakur
Datta Megha College of Engineering
Airoli, Navi Mumbai
neha.thakur@dmce.ac.in

Mr. Siddhesh Balsaraf
Datta Megha College of Engineering
Airoli, Navi Mumbai
Mumbai, Maharashtra

Ms. Priyanka Hanchate
Datta Megha College of Engineering
Airoli, Navi Mumbai
Mumbai, Maharashtra

Dr. S. D. Sawarkar
Datta Megha College of Engineering
Airoli, Navi Mumbai
Sudhir_sawarkar@yahoo.com

ABSTRACT: Transportation safety is important for the detection of Driver’s Drowsiness. Drowsy driving is an important reason for traffic accidents. Driver Fatigue is one of the big reasons causing most fatal road accidents around the world. This shows that in the transportation industry especially, where a heavy vehicle driver is often open to hours of monotonous driving which causes fatigue without frequent rest periods. Hence it is very essential to design a road accident prevention system for detecting driver’s drowsiness, which determines the level of driver inattention and gives a warning when an impending hazard exists. Real-time image processing, face/eye detection techniques, eye blink rates and yawning is used in a real-time system. The system is designed as an unobtrusive real-time monitoring system. The priority is on improving the safety of the driver without being meddlesome. The eye blink and yawning of the driver are detected. If the driver’s eyes remain closed for more than a certain period of time and the mouth of the driver is open for yawning, the driver is said to be drowsy and an alarm is sounded.

Key Words: Driver, Face Detection, Open-CV, Eye Detection, Yawning Detection, Drowsiness.

1.INTRODUCTION

One of the most predominant reasons that cause untimely deaths is road accidents. In the former case, the co-passenger would awake the driver of his/her lapse of attention and the driver would take measures to return to the required state of alertness. Many event in the news that report deaths and severe injuries caused by road accidents, mostly in the early morning period. A car hit another or careened into the roadblocks/boundaries. But what if the driver is alone or is driving in the night where there is a chance that the passengers are asleep. Driving under the influence of drowsiness is the root cause of over 100,000 road accidents every year. This amounts to a 2.2% death rate worldwide Microsleep is a temporary lapse in consciousness that may last up to 30 seconds.

1.1 Problem Definition

Fatigue is a safety problem that has not yet been deeply addressed by any country in the world mainly because of its nature. Fatigue, in general, is very tough to measure or notice unlike alcohol and drugs, which have clear key indicators and tests that are available easily. Probably, the best solutions to this problem are consciousness about fatigue-related accidents and promoting drivers to admit fatigue when needed. The former is hard and much more high-priced to achieve, and the latter is not possible without the former as driving for long hours is very lucrative.

2. Proposed System

The Camera will detect the eye region and mouth region using facial coordinates. Based on eye aspect ratio and will choice region of interest for mouth.

A. Face detection

There are many features such as height, weights, face features, the threshold of face. threshold of face colors in Haar cascade classifier. It is developed with a lot of positive and negative samples. Depending upon positive sizes features will be extracted. Edge detection is applied based on Haar detection and array is used to store output from edge detector. Parallel processing is done by extracting eyes and mouth features of driver.

B. Facial mapping using Dlib

The dlib library ships with a Histogram of Oriented Gradients based face detector along with the Facial landmark. The facial landmarks produced by dlib are index able list.

ACCIDENT PREVENTION USING EYE DROWSINESS & YAWNING DETECTION
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