基于主动轮廓的梯度域车道标记检测

B. Lu, Chunli Miao, Hui Wang
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引用次数: 2

摘要

车道标志的提取是智能交通中基于视觉系统的关键步骤。本文提出了一种基于主动轮廓模型的车道检测方法。该模型是对梯度域经典C-V模型的改进。初始水平集曲线可以在图像的任何位置,而不会改变分割结果。为了选择车道标志轮廓,采用矩不变法进行形状分析。在真实场景图像上的实验结果表明,该算法能够准确地检测出车道标记。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lane Mark Detection with Active Contour for Gradient Domain
The extraction of lane mark is an essential step for several vision-based systems in intelligent transportation applications. In this paper, we propose a novel method for lane detection using a new active contour model. The new model is a modified version of the classical C-V model in gradient domain. The initial level set curve can be anywhere in the image without changing the segmentation result. To select the lane mark contour, moment invariant is utilized to make shape analysis. The experiment results on real scene image show that the proposed algorithm could detect lane mark accurately.
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