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Intelligent Driver Assistance through AI-based Lane and Object Detection System

  • Unique Paper ID: 170251
  • Volume: 11
  • Issue: 6
  • PageNo: 3261-3264
  • Abstract:
  • Drivers rely on visual cues for navigation, with road lines serving as constant guides for steering. A key objective of smart-driving vehicles is to automatically detect these lane lines using algorithms. Lane detection, however, remains a complex challenge that has captivated the computer vision community for many years. It is a multi-feature detection problem that both computer vision and machine learning algorithms continue to address with limited effectiveness. We present an image processing method based on the Hough Transform, Canny Edge Detection, and Object Detection. The primary objective is to utilize the Canny edge detection algorithm to identify features, followed by a method to detect lane lines in images or video. Given the inherent imperfections in images, determining the slope and intercept of lines by examining individual pixels presents significant complexity. The Hough Transform is employed to address this challenge, as it facilitates the identification of significant lines and connects discontinuous edge points within an image. Furthermore, Object Detection is implemented to identify vehicles in proximity to the detected lanes.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 6
  • PageNo: 3261-3264

Intelligent Driver Assistance through AI-based Lane and Object Detection System

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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