In this paper, we study several grayscale-based image segmentation methods for real-time road sign recognition
applications on an FPGA hardware platform. The performance of different image segmentation algorithms in
different lighting conditions are initially compared using PC simulation. Based on these results and analysis,
suitable algorithms are implemented and tested on a real-time FPGA speed sign detection system. Experimental
results show that the system using segmented images uses significantly less hardware resources on an FPGA
while maintaining comparable system's performance. The system is capable of processing 60 live video frames
per second.
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