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Fast lane detection with Randomized Hough Transform

Azali Saudi, Jason Teo, Mohd Hanafi Ahmad Hijazi, Jumat Sulaiman

Year
2008
Citations
34

Abstract

Lane detection is an essential component of autonomous mobile robot applications. Any lane detection method has to deal with the varying conditions of the lane and surrounding that the robot would encounter while moving. Lane detection procedure can provide estimates for the position and orientation of the robot within the lane and also can provide a reference system for locating other obstacles in the path of the robot. In this paper we present a method for lane detection in video frames of a camera mounted on top of the mobile robot. Given video input from the camera, the gradient of the current lane in the near field of view are automatically detected. Randomized Hough Transform is used for extracting parametric curves from the images acquired. A priori knowledge of the lane position is assumed for better accuracy of lane detection.

Keywords

Hough transformComputer visionArtificial intelligenceComputer scienceMobile robotRobotOrientation (vector space)Position (finance)Parametric statisticsImage (mathematics)

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