Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Ikhlas Abdel-Qader
Dr. Raghvendra Geiji
Dr. Azim Houshyar
Dr. Osama Abudayyeh
Masters Thesis-Open Access
The U.S. Department of Transportation reports that on average there are 5,870,000 vehicle accidents each year. Twenty-three percent (23%) of these accidents are attributed to weather conditions with an annual average of more than 6,000 people are killed and 480,000 people are injured. Weather-related accidents occur mainly because of the low visibility on the roads under inclement conditions such as snow, rain and fog. While these conditions can be predictable and individuals try to avoid driving in inclement weather, there are circumstances that require driving in such conditions such as emergency responders or when the severity of the storm has not been predicted appropriately. In this thesis, we focus on improving driver's visibility through snow storms. A novel framework for a driver's assistance system has been proposed and implemented to reduce visibility degradations due to snow using videos captured from a dashboard camera. The framework for the system is composed of 4 stages using morphological operations and pre-and post-processes to address different visibility degradations and varying weather conditions. The proposed methodology has been validated using real life videos. The technique can be expanded in the future to address other types of inclement weather such as heavy rain, sand storms, and fog.
Hussein, Saleem Farhood, "Morphology Based Framework for Improved Driver's Visibility in Inclement Weather Conditions" (2015). Master's Theses. 659.