From Framework to Functionality: Exploring JavaScript and AI Integration in Automated Coloring
This article presents an automated coloring system that synergizes JavaScript and Artificial Intelligence (AI) technologies to enhance user experience, drive educational innovation, and improve creative efficiency. The implementation details include using the Canvas element and the Huemint color model to achieve AI coloring, covering steps such as loading layer data, sorting block sizes, monitoring mouse/touch inputs, tool selection, and coloring logic. Additionally, the study outlines appropriate color models for various scenarios and evaluates the advantages and limitations of different techniques. The results demonstrate how a resource-efficient approach can integrate JavaScript and AI technologies to deliver a flexible and efficient automated coloring solution.
Authors
- Su Seong Lee (ORCID: https://orcid.org/0000-0002-2968-5707)
- Wei-Han Chen (ORCID: https://orcid.org/0009-0002-0293-2322)
- Cheng-Yuan Ho (ORCID: https://orcid.org/0000-0002-6866-0633)
- K. F. Chen (ORCID: https://orcid.org/0000-0003-1304-3782)
- Yong Gong (ORCID: https://orcid.org/0000-0001-8964-1944)
- Wei‐An Chen (ORCID: https://orcid.org/0000-0001-9087-5414)
- Yu-Ting Gong
Institutions
- National Taiwan University (TW)
- National Taipei University of Business (TW)
- National Taipei University (TW)
Publication Details
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/mlhmi66056.2025.00023
- Primary Topic
- Color perception and design
- Type
- article
- Field-Weighted Citation Impact
- 0.00