Image Vectorization via Gradient Reconstruction

We present a fully automated technique that segments raster images into smooth shaded regions and reconstructs them using an optimal mix of solid fills, linear gradients, and radial gradients. Our method leverages a novel discontinuity‐aware segmentation strategy and gradient reconstruction algorith...

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Vydáno v:Computer graphics forum Ročník 44; číslo 2
Hlavní autoři: Chakraborty, Souymodip, Batra, Vineet, Phogat, Ankit, Jain, Vishwas, Ranawat, Jaswant Singh, Dhingra, Sumit, Wampler, Kevin, Fisher, Matthew, Lukáč, Michal
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.05.2025
Témata:
CCS Concepts
Computing methodologies → Image processing
Curves
Image reconstruction
Raster
Shading
ISSN:0167-7055, 1467-8659
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Abstract We present a fully automated technique that segments raster images into smooth shaded regions and reconstructs them using an optimal mix of solid fills, linear gradients, and radial gradients. Our method leverages a novel discontinuity‐aware segmentation strategy and gradient reconstruction algorithm to accurately capture intricate shading details and produce compact Bézier curve representations. Extensive evaluations on both designer‐created art and generative images demonstrate that our approach achieves high visual fidelity with minimal geometric complexity and fast processing times. This work offers a robust and versatile solution for converting detailed raster images into scalable vector graphics, addressing the evolving needs of modern design workflows.
AbstractList We present a fully automated technique that segments raster images into smooth shaded regions and reconstructs them using an optimal mix of solid fills, linear gradients, and radial gradients. Our method leverages a novel discontinuity‐aware segmentation strategy and gradient reconstruction algorithm to accurately capture intricate shading details and produce compact Bézier curve representations. Extensive evaluations on both designer‐created art and generative images demonstrate that our approach achieves high visual fidelity with minimal geometric complexity and fast processing times. This work offers a robust and versatile solution for converting detailed raster images into scalable vector graphics, addressing the evolving needs of modern design workflows.
Author Batra, Vineet
Ranawat, Jaswant Singh
Chakraborty, Souymodip
Wampler, Kevin
Dhingra, Sumit
Lukáč, Michal
Fisher, Matthew
Phogat, Ankit
Jain, Vishwas
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  surname: Lukáč
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10.1145/3592128
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Snippet We present a fully automated technique that segments raster images into smooth shaded regions and reconstructs them using an optimal mix of solid fills, linear...
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SubjectTerms CCS Concepts
Computing methodologies → Image processing
Curves
Image reconstruction
Raster
Shading
Title Image Vectorization via Gradient Reconstruction
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fcgf.70055
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Volume 44
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