• DocumentCode
    558982
  • Title

    Self-organizing segmentation for house object

  • Author

    Lee, Moonju ; Lee, Sukhan

  • Author_Institution
    Dept. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
  • fYear
    2011
  • fDate
    26-29 Oct. 2011
  • Firstpage
    1082
  • Lastpage
    1084
  • Abstract
    Clustering is the basic and first step of a process in many different fields. Clustering has been researched for many years. K-means clustering method is one of famous algorithms. However it cannot determine how many clusters are needed. This algorithm overcomes a disadvantage of other clustering algorithms. This paper presents a new method. Our algorithm can choose clustering number automatically.
  • Keywords
    image segmentation; pattern clustering; house object; k-means clustering method; selforganizing segmentation; Clustering algorithms; Educational institutions; Image segmentation; Indexes; Object segmentation; Partitioning algorithms; Shape; Clustering; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Systems (ICCAS), 2011 11th International Conference on
  • Conference_Location
    Gyeonggi-do
  • ISSN
    2093-7121
  • Print_ISBN
    978-1-4577-0835-0
  • Type

    conf

  • Filename
    6106320
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=558982