IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3345037.html
   My bibliography  Save this article

Fractal Visual Art Graphic Design Based on Computer-Aided Algorithms

Author

Listed:
  • Qihao Zhou
  • Teng Liu
  • Guorong Wu
  • Xuhui Chen
  • Man Fai Leung

Abstract

Embedded machine vision algorithm development platform is of great significance. Based on the elaboration of visual communication design, this paper further details the design of fractal visual art graphics based on computer-aided algorithms to design edge detection schemes, where edges represent sudden changes in the signal and are able to characterize the rich information of an image. In response to the problems of poor robustness and difficult parameter selection of the currently widely used edge detection algorithms, the platform encapsulates joint edge detection graphic components in a higher-order processing library to achieve the requirements of high-precision detection and to realise enhanced edge detection effects. Finally, the experimental analysis shows that the proposed algorithm has a more accurate detection effect and can meet the user's high-precision detection requirements.

Suggested Citation

  • Qihao Zhou & Teng Liu & Guorong Wu & Xuhui Chen & Man Fai Leung, 2022. "Fractal Visual Art Graphic Design Based on Computer-Aided Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-7, May.
    • Handle: RePEc:hin:jnlmpe:3345037
    DOI: 10.1155/2022/3345037
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/3345037.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/3345037.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/3345037?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:3345037. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.