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Image vectorization using a sparse patch layout
- Source :
- Graphical Models, Vol 135, Iss , Pp 101229- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Mesh-based image vectorization techniques have been studied for a long time, mostly owing to their compactness and flexibility in capturing image features. However, existing methods often lead to relatively dense meshes, especially when applied to images with high-frequency details or textures. We present a novel method that automatically vectorizes an image into a sparse collection of Coons patches whose size adapts to image features. To balance the number of patches and the accuracy of feature alignment, we generate the layout based on a harmonic cross field constrained by image features. We support T-junctions, which keeps the number of patches low and ensures local adaptation to feature density, naturally complemented by varying mesh-color resolution over the patches. Our experimental results demonstrate the utility, accuracy, and sparsity of our method.
- Subjects :
- Vector graphics
Image vectorization
Science
Technology (General)
T1-995
Subjects
Details
- Language :
- English
- ISSN :
- 15240703
- Volume :
- 135
- Issue :
- 101229-
- Database :
- Directory of Open Access Journals
- Journal :
- Graphical Models
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f83b02bbde284e33a3eb1b05ae88cb75
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.gmod.2024.101229