Name
Abstract | ||
|---|---|---|
In this paper, we propose a new fusion strategy for scene text detection. The system is based on a single fully convolution network, which outputs the coordinates of text bounding boxes at multiple scales. We improve the performance of text detection by combining a fusion strategy. This strategy obtains precise text bounding boxes according to the confidence of candidate text boxes. It exhibits promising robustness and discriminative power by fusing text boxes. Experimental results on ICDAR2011 and ICDAR2013 datasets indicate the effectiveness and robustness of the proposed fusion strategy with an F-measure of 87%, which outperforms the base network 2%. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICPR.2018.8545482 | 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) |
Field | DocType | ISSN |
Computer vision,Pattern recognition,Convolution,Computer science,Feature extraction,Robustness (computer science),Artificial intelligence,Artificial neural network,Fuse (electrical),Detector,Discriminative model,Bounding overwatch | Conference | 1051-4651 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zheng Yu | 1 | 8 | 1.13 |
| Shujing Lyu | 2 | 2 | 4.43 |
| Yue Lu | 3 | 1617 | 101.51 |
| patrick s p wang | 4 | 303 | 47.66 |