Chakraborty, SouymodipBatra, VineetPhogat, AnkitJain, VishwasRanawat, Jaswant SinghDhingra, SumitWampler, KevinFisher, MatthewLukác, MichalBousseau, AdrienDay, Angela2025-05-092025-05-0920251467-8659https://doi.org/10.1111/cgf.70055https://diglib.eg.org/handle/10.1111/cgf70055We 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.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Image processingComputing methodologies → Image processing10.1111/cgf.7005511 pages