• DocumentCode
    3393356
  • Title

    Image segmentation algorithm based on feature fusion and cluster

  • Author

    Zhanguo Gao ; Li Yao ; Fengyu Duan

  • Author_Institution
    Coll. of Inf. Technol., Beihua Univ., Jilin, China
  • fYear
    2011
  • fDate
    19-22 Aug. 2011
  • Firstpage
    1086
  • Lastpage
    1089
  • Abstract
    In order to make balance between the effect and time consumption of image segmentation, an image segmentation algorithm based on feature fusion and cluster is proposed in this paper. Firstly, the segmentation granularity is obtained adaptively according to the coarseness of image; secondly, different features are extracted, multi features are fused and classified by K-means clustering, and the image can be segmented quickly. Experiments show that the proposed algorithm can segment image quickly, and the segmentation effect is good, which has verified the validity.
  • Keywords
    feature extraction; image segmentation; pattern clustering; feature cluster; feature extraction; feature fusion; image coarseness; image segmentation algorithm; k-means clustering; segmentation granularity; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Feature extraction; Image color analysis; Image segmentation; Signal processing algorithms; Clustering; Feature Fusion; Image Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
  • Conference_Location
    Jilin
  • Print_ISBN
    978-1-61284-719-1
  • Type

    conf

  • DOI
    10.1109/MEC.2011.6025655
  • Filename
    6025655