2023 Vol.6 Apr.N0.2

• Title: Lane detection method based on improved ant colony algorithm
• Name: LIU Yue1 ,YANG Hua1 ,WANG Qingzheng12
• Company: 1.College of Information Engineering, Kaifeng University, Kaifeng 475000, China 2.School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240,China
• Abstract:

  The image is not de-noised during lane line detection, resulting in poor lane line detection effect. Therefore, this paper studies the lane line detection method based on improved ant colony algorithm. The vehicle-mounted camera acquires the image and corrects the distortion of the acquired road image. After the correction and preprocessing, the optimized ant colony algorithm with sensing function is used for image edge detection, and the detected edge information is used as the detection result of the lane line. The experimental results show that the detection accuracy of the proposed method is up to 97%, and the detection time is up to 34s, indicating that the proposed method is practical.

  
  

• Keyword: Distortion correction; Ant colony Image edge; Lane line detection
• DOI: 10.12250/jpciams2023090415
• Citation form: LIU Yue.Lane detection method based on improved ant colony algorithm [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.75-77

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