Name
Abstract | ||
|---|---|---|
Uyghur text localization in complex background images is a significant research for Uyghur image content analysis. In this paper, we propose a robust Uyghur text localization method in complex background images and provide a CPU–GPU heterogeneous parallelization scheme. Firstly, a multi-color-channel enhanced maximally stable extremal region is used to extract components in images, which is robust to blur and low contrast. Secondly, a two-stage component classification system is used to filter out non-text components. Finally, a component connected graph algorithm is proposed to construct text lines. Experiments on the proposed dataset demonstrate that our algorithm compares favorably with the state-of-the-art algorithms when handling Uyghur texts. Besides, the heterogeneous parallel implementation achieves 12.5 times speedup. |
Year | DOI | Venue |
|---|---|---|
2017 | https://doi.org/10.1007/s00138-017-0837-3 | Mach. Vis. Appl. |
Keywords | Field | DocType |
Uyghur,Text localization,Enhanced MSERs,CPU–GPU heterogeneous parallelization | Computer vision,Pattern recognition,Computer science,Image content,Artificial intelligence,Connectivity,Speedup | Journal |
Volume | Issue | ISSN |
28 | 7 | 0932-8092 |
Citations | PageRank | References |
5 | 0.42 | 33 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun Song | 1 | 5 | 0.42 |
| Jianjun Chen | 2 | 17 | 15.90 |
| Hongtao Xie | 3 | 439 | 47.79 |
| Zhineng Chen | 4 | 192 | 25.29 |
| Xingyu Gao | 5 | 17 | 2.29 |
| Xi Chen | 6 | 226 | 49.58 |