Grayscale image segmentation for real-time traffic sign recognition: the hardware point of view

Tam P. Cao; Guang Deng; Darrell Elton

doi:10.1117/12.810760

4 February 2009 Grayscale image segmentation for real-time traffic sign recognition: the hardware point of view

Tam P. Cao, Guang Deng, Darrell Elton

Proceedings Volume 7244, Real-Time Image and Video Processing 2009; 724405 (2009) https://doi.org/10.1117/12.810760
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

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.

Citation Download Citation

Tam P. Cao, Guang Deng, and Darrell Elton "Grayscale image segmentation for real-time traffic sign recognition: the hardware point of view", Proc. SPIE 7244, Real-Time Image and Video Processing 2009, 724405 (4 February 2009); https://doi.org/10.1117/12.810760

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