Do You Like Sclera? Sclera-region Detection and Colorization for Anime Character Line Drawings
- https://doi.org/10.2991/ijndc.k.190711.001How to use a DOI?
- Line drawing, colorization, sclera region, segmentation
Colorizing line drawings requires special skill, experience, and knowledge. Artists also spend a great deal of time and effort creating art. Given this background, research on automated line drawing colorization was recently conducted. However, the existing approaches present multiple problems, one of which is the inconsistency of the whites of the eyes (sclera) between line drawings and the results of colorizing. In particular, in line drawings, a person’s skin and sclera are often expressed in white. Hence, there are cases in which existing colorization methods cannot predict the boundary correctly. In this study, we propose automated colorization methods that use machine learning to segment sclera regions in grayscale line drawings. To improve the accuracy of previous automated colorization approaches, we implemented sclera-region detection and an automated colorizing approach on grayscale line drawings of people. In addition, we evaluated the colorization results created by our methods through a user study. Statistics show that our methods are somewhat superior to industrial application, but many of our respondents perceived little difference between the methods.
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Masashi Aizawa AU - Yuichi Sei AU - Yasuyuki Tahara AU - Ryohei Orihara AU - Akihiko Ohsuga PY - 2019 DA - 2019/07 TI - Do You Like Sclera? Sclera-region Detection and Colorization for Anime Character Line Drawings JO - International Journal of Networked and Distributed Computing SP - 113 EP - 120 VL - 7 IS - 3 SN - 2211-7946 UR - https://doi.org/10.2991/ijndc.k.190711.001 DO - https://doi.org/10.2991/ijndc.k.190711.001 ID - Aizawa2019 ER -