Straight-Line Detection Within 1 Millisecond Per Frame for Ultrahigh-Speed Industrial Automation

Songlin Du*, Ziwei Dong, Yuan Li, Takeshi Ikenaga


研究成果: Article査読

1 被引用数 (Scopus)


Detecting straight lines in video plays a fundamental role in camera-based industrial automation. With the increasing demands on production efficiency, detection speed has become one of the bottlenecks for highly efficient industrial automation. Because of data dependence and hardware limitations, existing vision systems based on central processing unit/graphics processing unit are unable to detect straight lines at an ultrahigh speed. This article addresses this problem and proposes a hardware-friendly Hough transform that can be implemented in fully parallel for the ultrahigh-speed detection, because of the following two key features: it processes multiple pixels in parallel and directly calculates line parameters while capturing the current frame; and it simultaneously initializes the Hough parameter space and votes in the Hough parameter space without any delay. Based on the proposed hardware-friendly Hough transform, its chip-level implementation and system-level hardware design are presented. Experimental results show that the main benefits of the proposed architecture are in real-time performances at a high frame rate (784 frames/s) and an ultralow delay (0.7749 ms/frame).

ジャーナルIEEE Transactions on Industrial Informatics
出版ステータスPublished - 2023 4月 1

ASJC Scopus subject areas

  • 情報システム
  • 電子工学および電気工学
  • 制御およびシステム工学
  • コンピュータ サイエンスの応用


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