Penerapan Multi-Palette Color untuk Pemberian Saran Pemilihan Warna Tema Desain Visual Vektor

  • Suliswaningsih Universitas Amikom Purwokerto
  • Adam Prayogo Kuncoro Universitas Amikom Purwokerto
  • Ali Nur Ikhsan Universitas Amikom Purwokerto
  • Muhammad Thoriq Jamil Universitas Amikom Purwokerto
  • Syahrul Sani Universitas Amikom Purwokerto
Abstract views: 174 , PDF downloads: 148
Keywords: color recommendations, graphic design, multi-color palette, vector visual design

Abstract

In graphic design, many creative applications offer many templates. This design platform is suitable for creative designers and hobbyists such as marketers, bloggers, social media managers, etc. In a design workflow, users select a template and replace elements with their resources. Instead of creating one color palette for all elements, researchers extract multiple color palettes from each visual element in a graphic document and then combine them into a set of colors. Researchers design sample color schemes to complement color sets and we recommend colors that might be determined based on the color context in a multi-palette. Researchers conducted model training and created a color recommendation system for a collection of vector visual designs. The proposed color recommendation method is targeted to be a color prediction medium, as well as a color recommendation system on vector media. The results of this study are in the form of color recommendations for vector graphic design based on a multi-palette of visual elements.

 

References

N. A. Haris, K. Kusrini, and H. Al Fatta, “Pengaruh Ciri Tekstur Pada Metode Klasifikasi LVQ Untuk Hasil Akurasi Identifikasi Citra Batik Tradisional Solo,” Infotekmesin, vol. 11, no. 2, pp. 62–67, 2020.

M. Frackiewicz and H. Palus, “Efficient Color Quantization Using Superpixels,” Sensors, vol. 22, no. 16, Aug. 2022.

L. P. Yuan, Z. Zhou, J. Zhao, Y. Guo, F. Du, and H. Qu, “InfoColorizer: Interactive Recommendation of Color Palettes for Infographics,” IEEE Trans. Vis. Comput. Graph., vol. 28, no. 12, pp. 4252–4266, Dec. 2022.

R. Seva, K. Chinjen, N. Estoista, and J. A. Wu, “Indicator distance and color effects in comprehension of multiple time series graph,” 2020.

S. Kim and S. Choi, “Dynamic closest color warping to sort and compare palettes,” ACM Trans. Graph., vol. 40, no. 4, 2021.

B. Jann, “Color palettes for Stata graphics: an update,” 2022.

V. Lange, “MapColPal-a color palette generation and testing tool for thematic maps,” 2022.

J. Kuswanto, “PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS ANDROID MATA PELAJARAN DESAIN GRAFIS KELAS X,” 2021.

A. I. Purnamasari, A. Setiawan, and K. Kaslani, “Pengembangan Media Pembelajaran Tari Topeng Berbasis Android dengan Metode Analysis Design Development Implementation and Evaluation,” Infotekmesin, vol. 12, no. 1, pp. 1–8, 2021.

F. Fahminnansih, E. Rahmawati, and A. P. Wardhanie, “Pemanfaatan Aplikasi Canva Untuk Desain Grafis Dan Promosi Produk Pada Sekolah Islami Berbasis Kewirausahaan,” J. Pengabdi. dan Pemberdaya. Masy., vol. 2, no. 1, p. 51, 2021.

E. Junianto and M. Z. Zuhdi, “Penerapan Metode Palette untuk Menentukan Warna Dominan dari Sebuah Gambar Berbasis Android,” J. Inform., vol. 5, no. 1, 2018.

E. Tripustikasari and A. D. Septiadi, “Film Animasi Pengenalan Saham Dengan Metode Motion Graphic,” Infotekmesin, vol. 10, no. 02, pp. 65–69, 2019.

L. Bartram, A. Patra, and M. Stone, “Affective color in visualization,” in Conference on Human Factors in Computing Systems - Proceedings, 2017, vol. 2017-May, pp. 1364–1374.

A. Fachrozy and S. Wahyuni, “Penerapan Sinematografi Pada Penciptaan Film Fiksi Berjudul “ Juara “,” J. Mhs. Fak. Seni dan Desain, vol. 1, no. 1, pp. 353–362, 2020.

J. Devlin, M.-W. Chang, K. Lee, K. T. Google, and A. I. Language, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” Naacl-Hlt 2019, no. Mlm, pp. 4171–4186, 2018.

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Published
2024-01-22