Institute for Data Analysis and Visualization

In this study we test the idea of using a graphics processing unit (GPU) as an em- bedded co-processor for real-time speed-limit sign detection. We implement a sys- tem that operates in real-time within the computational limits of contemporary em- bedded general-purpose processors. The input to the system is a set of grayscale videos recorded from a camera mounted in a vehicle. We implement a new tech- nique to realize the radial symmetry transform e+-ciently using rendering primi- tives accelerated by graphics hardware to detect the location of speed-limit sign candidates. The system reaches up to 88% detection rate and runs at 33 frames per second on video sequences with VGA (640x480) resolution on an embedded system with an Intel Atom 230 @ 1.67 GHz and a Nvidia GeForce 9200M GS.