Curve lane detection based on the binary particle swarm optimization

Shoutao Li, Jingchun Xu, Wei Wei, Haiying Qi
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引用次数: 9

Abstract

The method of B-spline curve fitting linebased on the binary particle swarm optimization is presented in this paper. First, according to the characteristics of the vertical and transverse width of the line must be straight, to extract the lane line feature points, and sorting out the feature points. Then, we select the cubic B-spline curve to fit the curve lane, first the discrete bunary particle swarm algorithm to optimize the number n of the control points, then by the least square method to calculate the control points of B-spline curve, according to the B-spline crrve fitting out the corresponding curve line. In order todetect corners recognition performance in a variety of road conditions has carried on the experimental study and the results show that the method has great adaptability.
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基于二元粒子群优化的曲线车道检测
提出了基于二元粒子群优化的b样条曲线拟合方法。首先,根据直线的纵向和横向宽度必须是直线的特点,提取出车道线的特征点,并对特征点进行整理。然后,选择三次b样条曲线拟合曲线车道,首先采用离散二元粒子群算法优化控制点的个数n,然后采用最小二乘法计算b样条曲线的控制点,根据b样条曲线拟合出相应的曲线直线。为了检测角点识别在多种路况下的性能进行了实验研究,结果表明该方法具有很大的适应性。
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