10 April 2018 A lane line segmentation algorithm based on adaptive threshold and connected domain theory
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061521 (2018) https://doi.org/10.1117/12.2302478
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
Abstract
Before detecting cracks and repairs on road lanes, it’s necessary to eliminate the influence of lane lines on the recognition result in road lane images. Aiming at the problems caused by lane lines, an image segmentation algorithm based on adaptive threshold and connected domain is proposed. First, by analyzing features like grey level distribution and the illumination of the images, the algorithm uses Hough transform to divide the images into different sections and convert them into binary images separately. It then uses the connected domain theory to amend the outcome of segmentation, remove noises and fill the interior zone of lane lines. Experiments have proved that this method could eliminate the influence of illumination and lane line abrasion, removing noises thoroughly while maintaining high segmentation precision.
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Hui Feng, Hui Feng, Guo-sheng Xu, Guo-sheng Xu, Yi Han, Yi Han, Yang Liu, Yang Liu, } "A lane line segmentation algorithm based on adaptive threshold and connected domain theory", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061521 (10 April 2018); doi: 10.1117/12.2302478; https://doi.org/10.1117/12.2302478
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