• DocumentCode
    2097331
  • Title

    Hybrid Image Segmentation Using RPCCL Clustering and Region Merging

  • Author

    Li, Xinhui ; Shen, Runping ; Chen, Renxi

  • Author_Institution
    Sch. of Remote Sensing, Nanjing Univ. of Inf. & Sci. Technol., Nanjing, China
  • fYear
    2011
  • fDate
    17-18 Sept. 2011
  • Firstpage
    49
  • Lastpage
    53
  • Abstract
    Image segmentation is very important to image analysis and satisfying methods are still unfounded. In this paper, we propose a new hybrid segmentation approach based on rival penalized controlled competitive learning (RPCCL) and region merging scheme. In the first, we performed median filtering on input image, and then selected initial color centers by using color quantization technique. During the RPCCL clustering, we merged some close centers to reduce classes. In the end, small regions were merged to produce the final segmentation results. Compared to original RPCCL, our method can overcome over-segmentation and obtain better results.
  • Keywords
    data compression; image coding; image colour analysis; image segmentation; learning (artificial intelligence); pattern clustering; RPCCL clustering; color centers; color quantization technique; hybrid image segmentation; image analysis; region merging scheme; rival penalized controlled competitive learning; Clustering algorithms; Color; Educational institutions; Image color analysis; Image segmentation; Merging; Quantization; Clustering; RPCCL; Region Merging; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing & Information Services (ICICIS), 2011 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4577-1561-7
  • Type

    conf

  • DOI
    10.1109/ICICIS.2011.19
  • Filename
    6063190