Palazzolo, ChristopherKaick, Oliver vanMould, DavidChristie, MarcHan, Ping-HsuanLin, Shih-SyunPietroni, NicoSchneider, TeseoTsai, Hsin-RueyWang, Yu-ShuenZhang, Eugene2025-10-072025-10-072025978-3-03868-295-0https://doi.org/10.2312/pg.20251296https://diglib.eg.org/handle/10.2312/pg20251296We propose a new method for synthesizing an arbitrarily sized novel vector texture given a single raster exemplar. In an analysis phase, our method first segments the exemplar to extract primary textons, secondary textons, and a palette of background colors. Then, it clusters the primary textons into categories based on visual similarity, and computes a descriptor to capture each texton's neighborhood and inter-category relationships. In the synthesis phase, our method first constructs a gradient field with a set of control points containing colors from the background palette. Next, it places primary textons based on the descriptors, in order to replicate a similar texton context as in the exemplar. The method also places secondary textons to complement the background detail. We compare our method to previous work with a wide range of perceptual-based metrics, and show that we are able to synthesize textures directly in vector format with quality similar to methods based on raster image synthesis.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → TexturingComputing methodologies → Texturing10.2312/pg.2025129612 pages