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Linear fuzzy space based road lane model and detection

机译：基于线性模糊空间的车道模型与检测

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摘要

In this paper, we propose a new road lane model based on linear fuzzy space mathematics, coupled with a robust road lane detection method using fuzzy c-means clustering. The fuzzy line based road lane model presented here describes a lane as a set of fuzzy collinear fuzzy points. The proposed algorithm for road line detection is able to deal with imprecise data and enables reduced computational complexity (proportional to the number of fuzzy points multiplied by the number of fuzzy lines) versus a standard Hough transformation. Experimental results show that the proposed method is fast, and robust enough for use in real-time applications. The proposed method has been implemented as an Android-based mobile phone application.
机译：本文提出了一种基于线性模糊空间数学的道路车道模型，并结合了一种基于模糊c均值聚类的鲁棒道路车道检测方法。此处介绍的基于模糊线的道路车道模型将车道描述为一组模糊共线模糊点。所提出的用于道路线检测的算法能够处理不精确的数据，并且与标准的霍夫变换相比，能够降低计算复杂度（与模糊点的数量乘以模糊线的数量成比例）。实验结果表明，该方法具有足够的鲁棒性，可以在实时应用中使用。所提出的方法已经实现为基于Android的手机应用程序。

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  • 来源
    《Knowledge-Based Systems》 |2013年第1期|37-47|共11页
  • 作者

    D. Obradovic; Z. Konjovic; E. Pap; I.J. Rudas;

  • 作者单位

    Faculty of Technical Sciences, Department of Computing and Automation, 21000 Novi Sad, Serbia;

    Faculty of Technical Sciences, Department of Computing and Automation, 21000 Novi Sad, Serbia;

    Faculty of Sciences, Department of Mathematics and Informatics, 21000 Novi Sad, Serbia,Obuda University, Institute of Intelligent Engineering Systems, H-1034 Budapest, Hungary;

    Obuda University, Institute of Intelligent Engineering Systems, H-1034 Budapest, Hungary;

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  • 正文语种 eng
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  • 关键词

    Lane model; Fuzzy point; Fuzzy line; Fuzzy collinear; Image processing; Line detection; Linear fuzzy space;

    机译：车道模型模糊点;模糊线;模糊共线;图像处理;线检测;线性模糊空间;

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