IDEAS home Printed from https://ideas.repec.org/a/ids/ijmtma/v37y2023i2p162-172.html
   My bibliography  Save this article

Intelligent colour selection method for product packaging design based on particle swarm optimisation

Author

Listed:
  • Jin Fan

Abstract

In order to solve the problems of poor correlation between image and colour matching and low user satisfaction in the traditional colour selection method of packaging design, a new colour intelligent selection method of product packaging design based on particle swarm optimisation algorithm is proposed in this paper. The colour intelligent selection parameters are calculated according to the hue value, the optimisation objective function of colour intelligent selection parameters is constructed, and the particle swarm optimisation algorithm is used to solve the objective function to complete the parameter optimisation. The correlation function of colour information clustering in packaging design is calculated, combined with the image colour enhancement algorithm, image brightness is adjusted, image detail contour is enhanced, and the intelligent selection of colour is completed. The experimental results show that this method is feasible in the intelligent colour selection of product packaging design, and the satisfaction scores are more than four points.

Suggested Citation

  • Jin Fan, 2023. "Intelligent colour selection method for product packaging design based on particle swarm optimisation," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 37(2), pages 162-172.
    • Handle: RePEc:ids:ijmtma:v:37:y:2023:i:2:p:162-172
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=131303
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijmtma:v:37:y:2023:i:2:p:162-172. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=21 .

    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.