Do You Like the Sclera?: Sclera-Region Detection in Line Drawings for Automated Colorization

Colorizing line drawings requires special skill, experience, and knowledge. Artists also spend a lot of time and effort creating artwork. Recently, given this background, research on the automated colorization of line drawings was actively conducted. However, there are multiple problems in the existing approaches, 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 the sclera are often expressed in white. Hence, there are cases where the boundary cannot be predicted correctly by previous studies. In this research, we propose automated colorization methods that segment sclera regions in grayscale line drawings using machine learning. In this paper, 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 the industrial application [1], but many of our results show that there is not much difference.