矢量化(数学)
计算机科学
仿射变换
算法
计算
虚假关系
绘图
计算机图形学
领域(数学分析)
矢量图形
拓扑(电路)
数学
人工智能
计算机图形学(图像)
组合数学
数学分析
机器学习
并行计算
纯数学
作者
Yuchen He,Sung Ha Kang,Jean‐Michel Morel
标识
DOI:10.1109/icip49359.2023.10222783
摘要
We propose a novel variational image vectorization algorithm (VIVA) which alternatively smooths contours by affine shortening flow and eliminates spurious regions by minimizing a Mumford-Shah-type functional. We introduce dual-primal graphs representing domain partitions which allows for effective iterative computation. The method provides varying levels of simplicity on the topology of the resulted vector graphics while effectively removing pixelization. It compares favorably to the state-of-the-art (SOTA) vectorization methods.
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