Paper Info
Title
XDoG: advanced image stylization with eXtended Difference-of-Gaussians
Abstract
Recent extensions to the standard Difference-of-Gaussians (DoG) edge detection operator have rendered it less susceptible to noise and increased its aesthetic appeal for stylistic depiction applications. Despite these advances, the technical subtleties and stylistic potential of the DoG operator are often overlooked. This paper reviews the DoG operator, including recent improvements, and offers many new results spanning a variety of styles, including pencil-shading, pastel, hatching, and binary black-and-white images. Additionally, we demonstrate a range of subtle artistic effects, such as ghosting, speed-lines, negative edges, indication, and abstraction, and we explain how all of these are obtained without, or only with slight modifications to an extended DoG formulation. In all cases, the visual quality achieved by the extended DoG operator is comparable to or better than those of systems dedicated to a single style.
Year
DOI
Venue
2011
10.1145/2024676.2024700
NPAR
Keywords
Field
DocType
recent improvement,aesthetic appeal,stylistic depiction application,advanced image stylization,extended difference-of-gaussians,extended dog operator,dog operator,extended dog formulation,binary black-and-white image,edge detection operator,stylistic potential,recent extension,edge detection,difference of gaussians
Computer vision,Computer graphics (images),Computer science,Edge detection,Edge detector,Depiction,Artificial intelligence,Operator (computer programming),Difference of Gaussians,Ghosting,Sketch
Conference
Citations 
PageRank 
References 
22
1.05
19
Authors
1
Name
Order
Citations
PageRank
Holger Winnemöller133019.35