Abstract
Data visualizers are usually experts in statistics and the field they involved. Most of them have lack of knowledge in arts. This leads to the condition where visualization created by them most of the time are not pleasant in terms of color, or they will be limited to the palette choices provided in the platform if they want to get a better output. This reduced the potential of visualization to act as an effective medium for marketing or awareness-raising purposes. In this paper, we study on the coding of colors in the way that is closer to human perception, together with the concept of color harmonization based on existing research. By integrating them, we get a framework that can retrieve the range of colors that looks harmony based on any request color. Our aim is to enhance the aesthetics and beauty of data visualization diagram through color modification. In the process of harmonizing the colors, our approach uses a distance scaling method on the hue dimension. This approach can better preserve the intended relationship between different colors from the original visualization. In most cases, the scaling process would be scale down, decreasing the distance between colors. Therefore, we need to take additional precautions to make sure that the scaled colors can still be perceived differently. We conducted a color difference calculation on all colors with the colors that are closest to them. Through the numerical method, we can set a minimum value and computationally identify that whether does the two colors are safe enough to distinguish. The visualization can perform an entire hue shifting process by adding a constant value to the hue of all colors after being harmonized through our approach. Our proposed approach helps data visualization artist or automated program to create a more color harmonized output, as well as providing the ability to freely change its entire color theme, which is useful to match the presenting environment, without needing to consider the problem of color difference.
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Acknowledgement
The authors would like to express appreciation for the support of the Fundamental Research Grant Scheme [FRGS/1/2019/SSI07/MMU/02/1] in providing adequate resource and guidance to complete this research.
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Lim, W.C., Wong, C.O., Wong, L.K. (2021). Color Aesthetic Enhancement for Categorical Data Visualization. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2021. Lecture Notes in Computer Science(), vol 13051. Springer, Cham. https://doi.org/10.1007/978-3-030-90235-3_2
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DOI: https://doi.org/10.1007/978-3-030-90235-3_2
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