An Improved FAST Corner Detection Algorithm for Real-Time Lane Lines Detection on Road Surface

  • Xiang Li
  • , Peng Wang*
  • , Yanrong Wang*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Detecting near lane lines presents challenges due to the influence of large noise blocks on the road surface. This study proposes an improved algorithm for realtime lane lines detection to counter this problem. The algorithm is carried out in three key steps: First, a minimum filter technique is performed to remove salt noise within the image. Subsequently, a modified Features from Accelerated Segment Test (FAST) corner detection algorithm is utilized to further filter and eliminate the block noise. Finally, Sobel edge detection algorithm is employed to achieve precise edge detection results for the lane lines. The proposed method has been deployed on a Field-Programmable Gate Array (FPGA), with comparative tests illustrating both its feasibility and effectiveness in practical application.

Original languageEnglish
Title of host publicationProceedings - 2023 8th International Conference on Communication, Image and Signal Processing, CCISP 2023
EditorsJing Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages276-280
Number of pages5
ISBN (Electronic)9798350305838
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event8th International Conference on Communication, Image and Signal Processing, CCISP 2023 - Hybrid, Chengdu, China
Duration: 17 Nov 202319 Nov 2023

Publication series

NameProceedings - 2023 8th International Conference on Communication, Image and Signal Processing, CCISP 2023

Conference

Conference8th International Conference on Communication, Image and Signal Processing, CCISP 2023
Country/TerritoryChina
CityHybrid, Chengdu
Period17/11/2319/11/23

Keywords

  • FAST corner detection
  • FPGA
  • Image processing
  • Sobel edge detection

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