driver drowsiness detection, Assignments of Digital Image Processing

driver ddriver drowsiness detection using image processing

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Drivers Sleepiness
Detection System
Idit Gershoni
Introduction to Computational and Biological Vision
Fall 2007
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Driver’s Sleepiness

Detection System

Idit Gershoni

Introduction to Computational and Biological Vision

Fall 2007

From Arizona Dept of Public

Safety campaign:

  • Time of occurrence of crashes in drivers at ages 26 to 45

in which the crashes were attributed by the police to the

driver being asleep (but in which alcohol was not judged to

be involved).

  • (^) The X axis is the time of day and the Y axis is the number

of crashes.

Motivation (2)

  • (^) Accidents study in the U.S (1990-92):
  • (^) Simulate sleepiness detection system

using image processing methods.

Project Goal

The (ideal) idea:

A video camera placed inside the car is

continuously filming the driver’s face

during the ride.

A detection system analyses the movie

frame by frame and determines whether

the driver’s eyes are open or shut.

If the eyes are shut for more than 1/4 a

second (longer than a normal blink

period) then the systems beeps to alert

the driver.

In Practice

  • (^) The system is only a simulation of such

detection system, and doesn’t perform real-

time detection & analysis.

  • (^) However, it does work on a given video file

with a given set of parameters.

Implementation – Step by Step (1)

  • (^) The movie is extracted to frames:

30 frames

per second

  • (^) Apply edge detector on each frame:

The Sobel edge detector

did the work

Implementation – Step by Step (2)

  • (^) Perform Circular Hough transform on each

frame in order to detect the irises:

Implementation – Step by Step (4)

  • (^) If irises not found – make a ‘beep’ sound

after not finding the irises in 8 consecutive

frames.

Implementation – Step by Step (5)

Future Work

Improving the algorithm:

 Study the location of the eyes in the first

image, and create a search area around

the eyes for the following frames.

 Performing Hough transform with a

range of possible radiuses.

Make the system work in real-time

environment.

Questions?