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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Veröffentlicht in:Computer graphics forum Jg. 44; H. 2
Hauptverfasser: Chakraborty, Souymodip, Batra, Vineet, Phogat, Ankit, Jain, Vishwas, Ranawat, Jaswant Singh, Dhingra, Sumit, Wampler, Kevin, Fisher, Matthew, Lukáč, Michal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.05.2025
Schlagworte:
CCS Concepts
Computing methodologies → Image processing
Curves
Image reconstruction
Raster
Shading
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.70055