, Assistant Professor, UMD-Electrical Engineering
Intelligent transportation systems depend on being able to track vehicle operations and collect accurate traffic data. This project targeted a hardware-based video detection system for real-time vehicle detection. To allow real-time detection, customized hardware implementation of the system is targeted instead of the traditional computer-based
implementation. The system includes four main processing steps. First, a camera is used to capture images. Second, the captured images are segmented using the Mixture-of-Gaussian algorithm. (Without sacrificing the segmentation accuracy, researchers modified the Mixture-of-Gaussian algorithm to allow more efficient and economical hardware implementation in terms of design overhead and hardware resources.) Third, the segmentation regions are extracted and validated as the objects of interest. In the last step, the validation result is wirelessly transmitted to a variable message sign, which displays necessary traffic information.
- Project number: 2010008
- Start date: 06/2009
- Project status: Completed
- Research area: Transportation Safety and Traffic Flow
Data and modeling, Vision Systems