dc.contributor.author | Rosin, Paul L. | en_US |
dc.contributor.author | Lai, Yu-Kun | en_US |
dc.contributor.editor | Donald House and Cindy Grimm | en_US |
dc.date.accessioned | 2016-02-18T10:14:05Z | |
dc.date.available | 2016-02-18T10:14:05Z | |
dc.date.issued | 2013 | en_US |
dc.identifier.isbn | 978-1-4503-2203-4 | en_US |
dc.identifier.issn | 1816-0859 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1145/2487276.2487280 | en_US |
dc.description.abstract | Colour is an important aspect of art. Not only does it give richness to images, but it always provides a means to highlight certain objects. This idea of spot colour has been used extensively in both fine art and commercial illustrations. Many non-photorealistic rendering (NPR) algorithms produce grayscale or monochromatic images with low saturations. In this paper we introduce the idea of spot colour to NPR and propose a simple and automatic algorithm to add spot colour to these rendering styles. The hue is thresholded into colour layers and the most appropriate layer is automatically determined based on factors such as layer region shape and salience. We also consider using an edge-based criterion to colourise the background, which is an effective means of making the foreground stand out. We demonstrate the effectiveness of our approach by adding spot colour to a diverse set of NPR styles. | en_US |
dc.publisher | ACM | en_US |
dc.subject | CR Categories | en_US |
dc.subject | I.3.3 [Computer Graphics] | en_US |
dc.subject | Picture/Image Generation | en_US |
dc.subject | I.3.6 [Computer Graphics] | en_US |
dc.subject | Methodology and Techniques. Keywords | en_US |
dc.subject | non | en_US |
dc.subject | photorealistic rendering | en_US |
dc.subject | image abstraction | en_US |
dc.subject | colour | en_US |
dc.subject | segmentation | en_US |
dc.title | Non-Photorealistic Rendering with Spot Colour | en_US |
dc.description.seriesinformation | Computational Aesthetics in Graphics, Visualization, and Imaging | en_US |
dc.description.sectionheaders | Image Processing / Vision | en_US |
dc.identifier.doi | 10.1145/2487276.2487280 | en_US |
dc.identifier.pages | 67-76 | en_US |