Field-aligned quadrangulation for image vectorization
Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature-aligned quad-dominant meshes. Inspired by the quadrangulation methods in 3D geometry proce...
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sg-ntu-dr.10356-1519632021-07-08T02:59:29Z Field-aligned quadrangulation for image vectorization Wei, Guangshun Zhou, Yuanfeng Gao, Xifeng Ma, Qian Xin, Shiqing He, Ying School of Computer Science and Engineering Engineering::Computer science and engineering Computer Graphics Image Processing Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature-aligned quad-dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400×400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications. Ministry of Education (MOE) The research of Yuanfeng Zhou was supported by the NSFC Fund (No.61772312), the key research and development project of Shandong province (2017GGX10110), the fundamental research funds of Shandong University (2018JC030). The research of Shiqing Xin was supported by the NSFC Fund (No.61772016).The research of Ying He was supported by the Singapore Ministry of Education Grant RG26/17. 2021-07-08T02:59:29Z 2021-07-08T02:59:29Z 2019 Journal Article Wei, G., Zhou, Y., Gao, X., Ma, Q., Xin, S. & He, Y. (2019). Field-aligned quadrangulation for image vectorization. Computer Graphics Forum, 38(7), 171-180. https://dx.doi.org/10.1111/cgf.13826 0167-7055 https://hdl.handle.net/10356/151963 10.1111/cgf.13826 2-s2.0-85075086219 7 38 171 180 en RG26/17 Computer Graphics Forum © 2019 The Author(s). Computer Graphics Forumc © 2019 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. All rights reserved. |
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Engineering::Computer science and engineering Computer Graphics Image Processing Wei, Guangshun Zhou, Yuanfeng Gao, Xifeng Ma, Qian Xin, Shiqing He, Ying Field-aligned quadrangulation for image vectorization |
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Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature-aligned quad-dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400×400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Wei, Guangshun Zhou, Yuanfeng Gao, Xifeng Ma, Qian Xin, Shiqing He, Ying |
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Article |
author |
Wei, Guangshun Zhou, Yuanfeng Gao, Xifeng Ma, Qian Xin, Shiqing He, Ying |
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Wei, Guangshun |
title |
Field-aligned quadrangulation for image vectorization |
title_short |
Field-aligned quadrangulation for image vectorization |
title_full |
Field-aligned quadrangulation for image vectorization |
title_fullStr |
Field-aligned quadrangulation for image vectorization |
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Field-aligned quadrangulation for image vectorization |
title_sort |
field-aligned quadrangulation for image vectorization |
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2021 |
url |
https://hdl.handle.net/10356/151963 |
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1705151312387112960 |