• DocumentCode
    419685
  • Title

    Efficient coding of stroke-rendered paintings

  • Author

    Kovacs, Levente ; Szirányi, Tamás

  • Author_Institution
    Veszprem Univ., Hungary
  • Volume
    2
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    835
  • Abstract
    There are more and more applications of non-photorealistic rendered images, sketches and drawings. Several techniques for generating such imagery are widely known. The stochastic painting-based painterly image (and video) generation presented herein is a multi-purpose image rendering and representation method, suitable for many purposes: painterly rendering, storing, compression or indexing. It incorporates many new features like multiscale edge following, stroke-set optimizations, templates, color morphology, etc. We demonstrate that the presented technique (called enhanced stochastic paintbrush transformation or eSPT) is suitable for fast high quality painterly rendering, providing good lossless painted compression ratios and features that make it suitable for many applications. One of these we wish to emphasize is the suitability to code painted images in a way that does not introduce any coding artifacts (blockiness, ringings, etc.) but provides a compact form of representation that still retains the main property of a painting: that it is a painting after all.
  • Keywords
    data compression; image coding; image colour analysis; image representation; optimisation; stochastic processes; color morphology; enhanced stochastic paintbrush transformation; multipurpose image representation method; multiscale edge; nonphotorealistic rendered images; painted compression ratios; stochastic painting; stroke-rendered paintings coding; stroke-set optimizations; Brushes; Image coding; Image generation; Indexing; Morphology; Painting; Rendering (computer graphics); Shape control; Stochastic processes; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334388
  • Filename
    1334388