Abstract
Cartoons are a worldwide popular visual entertainment medium with a long history. Nowadays, with the boom of electronic devices, there is an increasing need to digitize old classic cartoons as a basis for further editing, including deformation, colorization, etc. To perform such editing, it is essential to extract the structure lines within cartoon images. Traditional edge detection methods are mainly based on gradients. These methods perform poorly in the face of compression artifacts and spatially-varying line colors, which cause gradient values to become unreliable. This paper presents the first approach to extract structure lines in cartoons based on regions. Our method starts by segmenting an image into regions, and then classifies them as edge regions and non-edge regions. Our second main contribution comprises three measures to estimate the likelihood of a region being a non-edge region. These measure darkness, local contrast, and shape. Since the likelihoods become unreliable as regions become smaller, we further classify regions using both likelihoods and the relationships to neighboring regions via a graph-cut formulation. Our method has been evaluated on a wide variety of cartoon images, and convincing results are obtained in all cases.
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Xiangyu Mao received his B.S. degree in computer science from The Chinese University of Hong Kong in 2012. He is currently a Ph.D. candidate in the Department of Computer Science and Engineering, The Chinese University of Hong Kong. His research interests include computer graphics, computer vision, computational manga and anime, and nonphotorealistic rendering.
Xueting Liu received her B.S. degree from Tsinghua University and Ph.D. degree from The Chinese University of Hong Kong in 2009 and 2014, respectively. She is currently a postdoctoral research fellow in the Department of Computer Science and Engineering, The Chinese University of Hong Kong. Her research interests include computer graphics, computer vision, computational manga and anime, and non-photorealistic rendering.
Tien-Tsin Wong received his B.S., M.Phil., and Ph.D. degrees in computer science from The Chinese University of Hong Kong in 1992, 1994, and 1998, respectively. He is currently a professor in the Department of Computer Science and Engineering, The Chinese University of Hong Kong. His main research interests include computer graphics, computational manga, precomputed lighting, image-based rendering, GPU techniques, medical visualization, multimedia compression, and computer vision. He received the IEEE Transactions on Multimedia Prize Paper Award in 2005 and the Young Researcher Award in 2004.
Xuemiao Xu received her B.S. and M.S. degrees in computer science and engineering from South China University of Technology in 2002 and 2005, respectively, and Ph.D. degree in computer science and engineering from The Chinese University of Hong Kong in 2009. She is currently an associate professor in the School of Computer Science and Engineering, South China University of Technology. Her research interests include image similarity measurement, digital manga and cartoons, intelligent transportation based on image analysis, and biometric recognition.
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Mao, X., Liu, X., Wong, TT. et al. Region-based structure line detection for cartoons. Comp. Visual Media 1, 69–78 (2015). https://doi.org/10.1007/s41095-015-0007-3
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DOI: https://doi.org/10.1007/s41095-015-0007-3