Fpga/python co-design for lane line detection on a pynq-z1 board

Koki Honda, Kaijie Wei, Hideharu Amano

研究成果: Conference contribution

抄録

This paper presents the implementation of lane line detection on FPGA and Python. Lane line detection consists of three functions, median blur, adaptive threshold, and Hough transform. We implemented only accumulation of Hough transform on FPGA. Although the Hough transform cannot be implemented on a low-end FPGA board if implemented directly, by reducing ρθ space, it was successfully implemented on a low-end FPGA board. The rest of the Hough transform was implemented using Python's NumPy and SciPy, and OpenCV. Although it was very easy to write, it did not become a bottleneck for the whole process because of its effectiveness. As a result, we could achieve a 3.9x speedup compared to OpenCV and kept the developing cost down. When implementing median blur and adaptive threshold on an FPGA, we could achieve a 6.34x speedup.

本文言語English
ホスト出版物のタイトルProceedings - 2019 IEEE 13th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ53-60
ページ数8
ISBN(電子版)9781728148823
DOI
出版ステータスPublished - 2019 10
イベント13th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2019 - Singapore, Singapore
継続期間: 2019 10 12019 10 4

出版物シリーズ

名前Proceedings - 2019 IEEE 13th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2019

Conference

Conference13th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2019
国/地域Singapore
CitySingapore
Period19/10/119/10/4

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 電子工学および電気工学
  • 制御と最適化

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