Artistic Color Matching Technology Based on Silhouette Coefficient and Visual Perception

Now-a-days, traditional color matching methods cannot meet the current market demand. Meanwhile, there are many factors to consider in the design, which affect the design efficiency. Therefore, it is necessary to seek more efficient design methods. So, this study proposed an improved K-Means based on silhouette coefficients and designed an image main color adaptive extraction model. Subsequently, an evaluation method for artistic color matching schemes based on visual perception and similarity measurement was introduced. Finally, Pix2Pix based on visual aesthetics was designed to develop color matching schemes. These results confirmed that in the objective evaluation of the main color extraction results, the structural similarity of the main color images generated using the silhouette coefficient was superior to other methods. The maximum structural similarity of this method was 0.675, with an average of 0.663. Meanwhile, the peak signal-to-noise ratio of the main color image generated by this method reached a maximum of 21.49 dB, with an average of 21.05 dB. In the validation of Pix2Pix based on visual aesthetics, the average color palette similarity of Pix2Pix's design scheme based on visual aesthetics was 0.807. Meanwhile, the average comprehensive evaluation index of this method was 0.798, which was better than Pix2Pix without integrating visual aesthetics. In the experimental verification of computational efficiency, the average color matching time of the Pix2Pix network model based on visual aesthetics is only 13.75ms. The average time consumption of the K-Means clustering algorithm model is as high as 135.67ms. Overall, the designed image main color adaptive extraction model and color matching model have strong practical applicability. These methods provide effective auxiliary design solutions for the design and development of artistic products, which helps to improve design efficiency.

@article{Li2024,
  title     = {Artistic Color Matching Technology Based on Silhouette Coefficient and Visual Perception},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Huizhou Li and Wubin Zhu},
  doi       = {10.14569/IJACSA.2024.0150642},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150642}
}