Project Type
group
Authors' Class Standing
Senior
Lead Presenter's Name
Alex Bassett
Faculty Mentor Name
Ilteris Demirkiran
Abstract
Locating a parking space at the Embry-Riddle Aeronautical University Daytona Beach campus is a time-consuming feat for students, faculty, and staff members. This research project designs a system that identifies the status of the individual parking spaces on campus, and pushes the data to a mobile device application. Users can use this application to locate a free parking space, or see which parking lots are full. The approach taken for this project uses live feed from an IP camera, which is imported to the MATLAB environment. The real-time system uses image subtraction and feature detection to determine if there is a vehicle in a parking spot. This is accomplished by subtracting a recent image from its predecessor, and comparing the mean value of the RGB pixels to the mean value calculated in the previous iteration. This system constantly refreshes over a short time interval to constantly keep the user informed on the status of parking lots on campus. The system successfully identifies the status of the parking lots on campus; therefore, integration of this system will help regulate on-campus traffic, and reduce the stress associated with the parking situation for all students, faculty, and staff members.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
Yes, Ignite Grant
Detection and Identification of Parking Spots on the ERAU Campus using Image Processing Techniques
Locating a parking space at the Embry-Riddle Aeronautical University Daytona Beach campus is a time-consuming feat for students, faculty, and staff members. This research project designs a system that identifies the status of the individual parking spaces on campus, and pushes the data to a mobile device application. Users can use this application to locate a free parking space, or see which parking lots are full. The approach taken for this project uses live feed from an IP camera, which is imported to the MATLAB environment. The real-time system uses image subtraction and feature detection to determine if there is a vehicle in a parking spot. This is accomplished by subtracting a recent image from its predecessor, and comparing the mean value of the RGB pixels to the mean value calculated in the previous iteration. This system constantly refreshes over a short time interval to constantly keep the user informed on the status of parking lots on campus. The system successfully identifies the status of the parking lots on campus; therefore, integration of this system will help regulate on-campus traffic, and reduce the stress associated with the parking situation for all students, faculty, and staff members.