首页> 外文会议>International Conference on Graphic and Image Processing >A Lane Line Segmentation Algorithm Based on Adaptive Threshold and Connected Domain Theory
【24h】

A Lane Line Segmentation Algorithm Based on Adaptive Threshold and Connected Domain Theory

机译:一种基于自适应阈值和连接域理论的车道线分割算法

获取原文

摘要

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.
机译:在检测道路车道上的裂缝和维修之前,有必要消除车道线对道路车道图像识别结果的影响。旨在瞄准由车道线引起的问题,提出了一种基于自适应阈值和连接域的图像分割算法。首先,通过分析灰度分布等特征和图像的照明,算法使用Hough变换将图像划分为不同的部分并分别将它们转换为二进制图像。然后,它使用连接的域理论来修改分割的结果,去除噪声并填充车道线的内部区域。实验证明,该方法可以消除照明和车道线磨损的影响,在保持高分割精度的同时彻底去除噪声。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号