Name
Abstract | ||
|---|---|---|
In this article, we describe a general purpose system that, given as input a segmented/classified image, automatically provides different visual outputs exploiting solid colors, color boundaries, and transparent colors. Moreover, if the names of the classes are given, the system automatically places a textual label in the less salient sub-region of the corresponding class. For color-class association and class label placement, we take into account the underlying image color and structure exploiting both saliency and superpixel representation. The color selection and the color-class association are formulated both as optimization problems and heuristically solved using a Local Search procedure. Results show the effectiveness of the proposed system on images having different content and different number of annotated regions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1177/1473871617700682 | INFORMATION VISUALIZATION |
Keywords | Field | DocType |
Image segmentation, high-contrast colors, color-class association, optimization | Computer vision,Color-coding,Heuristic,Pattern recognition,Salience (neuroscience),Computer science,Image segmentation,Artificial intelligence,Local search (optimization),Contextual image classification,Optimization problem,Salient | Journal |
Volume | Issue | ISSN |
17 | 2 | 1473-8716 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simone Bianco | 1 | 226 | 24.48 |
| Raimondo Schettini | 2 | 1476 | 154.06 |