1. Vehicle Accidents Alarming System
Using Image Processing
A .A. V. D. Amarathunga (102005)
Supervisor : K.P. Vidanapathirana
Department of Electronics
Faculty of Applied Sciences
ASRITE 2015 30.04.2015
3. Introduction
Vehicle Accidents:
Traffic collision Motor Vehicle Collision (MVC),
traffic accident, motor vehicle
accident, car accident, automobile
accident, road traffic collision, road
traffic accident, wreck, car crash,
or car smash occurs when a vehicle
collides with another vehicle.
ASRITE 2015 30.04.2015
4. Cause of Fatal Accidents:
Source : SIEMENS StudyASRITE 2015 30.04.2015
5. Preventing accidents:
Driver assisting systems(Outdoor solution)
Rules and regulations
Self disciplines of drivers
ASRITE 2015 30.04.2015
6. Driver Assisting Systems (DAS)
DAS Developed to automate/adapt/enhance vehicle systems for
safety and better driving
Safety features are designed to avoid collisions and accidents by
offering technologies that alert the driver to potential problems, or to
avoid collisions by implementing
safeguards and taking over control
of the vehicle
ASRITE 2015 30.04.2015
7. Existing Driver Assisting Systems:
Automate lighting
Adaptive cruise control
Automate braking
Incorporate GPS/ Traffic warnings
Connect to smart phones
Keep the driver in the correct lane
Warning on sleepiness
ASRITE 2015 30.04.2015
8. Technology used in the proposed system
Image Processing:
Form of Signal Processing
Input is Photograph or a Video
30.04.2015ASRITE 2015
9. pcDuino:
Mini PC platform
Runs with Ubuntu or Android OS
Compatible with Arduino interface
Cost effective
ASRITE 2015 30.04.2015
11. Python programming language:
General purpose
High level language
Easily understandable
In built libraries for image processing
Widely used
ASRITE 2015 30.04.2015
12. Open CV library:
Open source
It has C++, C, Python and Java interfaces
Supports Windows, Linux, Mac OS,
iOS and Android
In built libraries for image processing
Widely used
ASRITE 2015 30.04.2015
13. Design of the system
Vehicle Accidents Alarming System
Drivers drowsiness will be detected from eye
blinking rate
Uses Image Processing
Detects rate of eye blinking
Uses a night-vision camera
Can easily mount
Powered by cigarettes lighter
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18. Future Developments
Drivers eye blink rate can be identified using artificial
intelligence (AI)
Warning signal can be developed to vibrate the seat
of the driver or vibrate the steering wheel
ASRITE 2015 30.04.2015