Project Overview
Passenger safety is the primary concern and focus of automobile manufacturers today. In addition to the passive safety equipment, such as seatbelts and airbags, technology based active safety mechanisms are being developed and incorporated into all types of commercial and industrial vehicles and may soon be required by law. Current trends are requiring automobile manufacturers to include a multitude of technology based safety equipment including ultrasonic sensors and back-up cameras and even forward facing cameras. Historically, cameras placed in vehicles give the driver an unaltered view from behind the vehicle; however, with the sponsorship of Xilinx, Michigan State University’s ECE 480 Team 4 has designed and implemented algorithms that will detect and classify objects, allowing the driver to be alerted.
This system draws the driver’s attention to objects either behind or in front of the vehicle, by marking them with targets. In doing so, the driver will be less likely to overlook objects that may create a safety hazard. The team has combined the techniques of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) to create a system that will both accurately and efficiently detect and visually alert the driver to hazardous objects. Implementation of the algorithm utilizes Xilinx’s Spartan-3A Field Programmable Gate Array (FPGA) development board and Xilinx’s System Generator tools.