Abstract
In this paper, we propose an FPGA-based collision warning system for advanced automobile driver assistance systems or autonomous moving robots. The system consists of three function blocks: edge detection, moving-object detection and danger evaluation and collision warning. In the moving-object detection, the system uses a moving-object detection algorithm inspired by neuronal propagation in the hippocampus, which can run in high speed and low calculation cost. We have applied the system in a robot. It can detect moving objects with a speed range of 3-47cm/s with a sampling period of 33ms for an input image of 320×240 pixels, and can output a warning against dangerous regions in the input image.
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Liang, H., Suzuki, Y., Morie, T., Nakada, K., Miki, T., Hayashi, H. (2010). An FPGA-Based Collision Warning System Using Moving-Object Detection Inspired by Neuronal Propagation in the Hippocampus. In: Hanazawa, A., Miki, T., Horio, K. (eds) Brain-Inspired Information Technology. Studies in Computational Intelligence, vol 266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04025-2_26
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DOI: https://doi.org/10.1007/978-3-642-04025-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04024-5
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