Encoding-free incrementing hough transform for high frame rate and ultra-low delay straight-line detection

Ziwei Dong, Tingting Hu, Ryuji Fuchikami, Takeshi Ikenaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High frame rate and ultra-low delay straight-line detection plays an increasingly important role in highly automated factories that call for straight-line features to achieve swift locations in real scenes. However, vision systems based on CPU/GPU have a fixed delay between image capture and detection, making straight-line detection challenging to reach an ultra-low delay. Achieving detection nearly simultaneous with capture on the same image is considered. This paper proposes (A) an encoding-free incrementing Hough transform and (B) a partially compressed line parameter space to implement a straight-line detection core on an FPGA board. The encoding-free incrementing Hough transform directly calculates line parameters only by incrementing and initialization while capturing an image. Furthermore, the partially compressed line parameter space reduces the required memory resources and the path delay under the premise of accurate vote recordings for every line feature. The evaluation result shows that the proposals achieve as accurate detection (RMSE of θ on 0.0057, and RMSE of p on 2.09) as standard Hough transform (RMSE of θ on 0.0057, and RMSE of p on 2.13) and the designed detection core processes VGA (640 × 480) videos at 1.358 ms/frame delay.

Original languageEnglish
Title of host publicationProceedings of MVA 2021 - 17th International Conference on Machine Vision Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784901122207
DOIs
Publication statusPublished - 2021 Jul 25
Event17th International Conference on Machine Vision Applications, MVA 2021 - Aichi, Japan
Duration: 2021 Jul 252021 Jul 27

Publication series

NameProceedings of MVA 2021 - 17th International Conference on Machine Vision Applications

Conference

Conference17th International Conference on Machine Vision Applications, MVA 2021
Country/TerritoryJapan
CityAichi
Period21/7/2521/7/27

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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