• DocumentCode
    182915
  • Title

    Unstructured road detection based on fuzzy clustering arithmetic

  • Author

    Xiao Liu ; KeKe Shang ; Jie Liu ; Chun Yu Zhou

  • Author_Institution
    Coll. of Sci., Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    114
  • Lastpage
    118
  • Abstract
    The unstructured road detection plays a key role in an autonomous vehicle navigation system. However, the unstructured road images often contain shadows and are easily affected by ambient light, resulting to an inaccuracy with road detection. A robust road detection technique is required. In this paper, we adopted an improved fuzzy c-means(FCM) clustering algorithm to address these issues. The new technique considered the neighborhood impact factor when calculating distances between the cluster center and a pixel. Our experimental results show that the improved FCM have better outcomes.
  • Keywords
    fuzzy set theory; mobile robots; object detection; path planning; pattern clustering; remotely operated vehicles; ambient light; autonomous vehicle navigation system; fuzzy clustering arithmetics; improved FCM clustering algorithm; improved fuzzy c-means clustering algorithm; robust road detection technique; unstructured road detection; unstructured road images; Clustering algorithms; Color; Feature extraction; Image color analysis; Image segmentation; Roads; Robustness; HSV Color Space; cluster; fuzzy c-means; unstructured road detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4799-5147-5
  • Type

    conf

  • DOI
    10.1109/FSKD.2014.6980817
  • Filename
    6980817