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...

Full description

Saved in:
Bibliographic Details
Published in:Computer graphics forum Vol. 44; no. 2
Main Authors: Chakraborty, Souymodip, Batra, Vineet, Phogat, Ankit, Jain, Vishwas, Ranawat, Jaswant Singh, Dhingra, Sumit, Wampler, Kevin, Fisher, Matthew, Lukáč, Michal
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.05.2025
Subjects:
CCS Concepts
Computing methodologies → Image processing
Curves
Image reconstruction
Raster
Shading
ISSN:0167-7055, 1467-8659
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.70055