Automatic and topology-preserving gradient mesh generation for image vectorization

Lai, Yukun ORCID: https://orcid.org/0000-0002-2094-5680, Hu, Shi-Min ORCID: https://orcid.org/0000-0001-7507-6542 and Martin, Ralph Robert 2009. Automatic and topology-preserving gradient mesh generation for image vectorization. ACM Transactions on Graphics 28 (3) , 85. 10.1145/1531326.1531391

Preview

PDF Download (1MB) | Preview

Abstract

Gradient mesh vector graphics representation, used in commercial software, is a regular grid with specified position and color, and their gradients, at each grid point. Gradient meshes can compactly represent smoothly changing data, and are typically used for single objects. This paper advances the state of the art for gradient meshes in several significant ways. Firstly, we introduce a topology-preserving gradient mesh representation which allows an arbitrary number of holes. This is important, as objects in images often have holes, either due to occlusion, or their 3D structure. Secondly, our algorithm uses the concept of image manifolds, adapting surface parameterization and fitting techniques to generate the gradient mesh in a fully automatic manner. Existing gradient-mesh algorithms require manual interaction to guide grid construction, and to cut objects with holes into disk-like regions. Our new algorithm is empirically at least 10 times faster than previous approaches. Furthermore, image segmentation can be used with our new algorithm to provide automatic gradient mesh generation for a whole image. Finally, fitting errors can be simply controlled to balance quality with storage.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information:	Proceedings of ACM SIGGRAPH 2009 PDF uploaded in accordance with publisher's policy http://www.sherpa.ac.uk/romeo/issn/0730-0301/ [accessed 06/06/2015]
Publisher:	ACM
ISSN:	0730-0301
Funders:	EPSRC
Last Modified:	06 Nov 2023 15:04
URI:	https://orca.cardiff.ac.uk/id/eprint/27764

Citation Data

Cited 89 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item