Name
Abstract | ||
|---|---|---|
Color feature, as one of the low level features, plays important role in image processing, object recognition and other fields. For example, in the task of scene text detection and recognition, lots of methodologies employ features that utilize color contrast of text and the corresponding background for connected component extraction. However, the true distributions of text and its background, in terms of color, is still not examined because it requires an enough number of scene text database with pixel-level labelled text/non-text ground truth. To clarify the relationship between text and its background, in this paper, we aim at investigating the color non-parametric distribution of text and its background using a large database that contains 3018 scene images and 98,600 characters. The results of our experiments show that text and its background can be discriminated by means of color, therefore color feature can be used for scene text detection. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICDAR.2015.7333813 | International Conference on Document Analysis and Recognition |
Field | DocType | ISSN |
Color contrast,Computer vision,Color histogram,Pattern recognition,Computer science,Image processing,Ground truth,Connected component,Artificial intelligence,Text detection,Cognitive neuroscience of visual object recognition | Conference | 1520-5363 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Renwu Gao | 1 | 6 | 0.77 |
| Shoma Eguchi | 2 | 0 | 0.34 |
| Seiichi Uchida | 3 | 790 | 105.59 |