• DocumentCode
    2547859
  • Title

    An improved algorithm for auto-generating digital oil painting based on an accelerated K-means

  • Author

    Su, Qinghua ; Huang, Zhangcan ; Wang, Xiaohong ; Hu, Zongbo

  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    730
  • Lastpage
    733
  • Abstract
    The color quantization is the first and key step to auto-generate digital oil painting. In this paper, we apply an accelerated K-means based on the triangle equality to implement the image color quantization and then present an algorithm for auto-generating digital oil painting based on the accelerated K-means, called AkM-AgDOP. Comparing the traditional K-means, the accelerated K-means improves more greatly the convergence speed of the algorithm for auto-generating digital oil painting. And the numerical experiments also show that an original image could be transformed into a flowing line image and a better oil effective image with less distortion in color by AkM-AgDOP.
  • Keywords
    art; computational geometry; image colour analysis; quantisation (signal); AkM-AgDOP; accelerated k-means; color distortion; color quantization; digital oil painting auto-generation; flowing line image; image color quantization; triangle equality; Acceleration; Algorithm design and analysis; Clustering algorithms; Convergence; Image color analysis; Painting; Quantization; accelerated k-means; color quantization; digital oil painting; triangle inequality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6234086
  • Filename
    6234086