Abstract:
Driver Fatigue detection is an important
role in transportation for safety system. Driver
drowsiness has been one of the major causes of
road accidents and can lead to severe physical
injuries and deaths. This thesis presents a vision
based driver fatigue detection system for driving
safety and produce timely warnings that could
prevent accidents via android application. A
method for detecting sleepiness in drivers is
developed by using a smart phone camera that
point directly towards the driver’s face and
capture from the color video. In first step we use
color space for drivers’ face detection. Color
images with skin color in the chromatic and pure
color space YCrCb, which separates luminance
and chrominance components. Then,
mathematical morphological operators are used
to remove noisy regions. Blob detection finds the
maximum blob. Edge detection is employed to
locate the regions of the driver’s eyes, which are
used as the templates for eye state recognition in
subsequent frames. The template is correlated
with different regions of the face image. The
region of face which gives maximum correlation
with template refers to eye region. The method is
simple and easy to implement. Finally, the
recognized eyes’ images are used for fatigue
detection in order to generate warning alarms for
driving safety.
