Automatic text detection in video frames based on bootstrap artificial neural network and CED
| dc.contributor.author | Hao, Yan | |
| dc.contributor.author | Yi, Zhang | |
| dc.contributor.author | Zeng-guang, Hou | |
| dc.contributor.author | Min, Tan | |
| dc.contributor.editor | Skala, Václav | |
| dc.date.accessioned | 2013-04-16T09:37:50Z | |
| dc.date.available | 2013-04-16T09:37:50Z | |
| dc.date.issued | 2003 | |
| dc.description.abstract | In this paper, one novel approach for text detection in video frames, which is based on bootstrap artificial neural network (BANN) and CED operator, is proposed. This method first uses a new color image edge operator (CED) to segment the image and achieve the elementary candidate text block. And then the neural network is introduced into the further classification of the text blocks and the non-text blocks in video frames. The idea of bootstrap is introduced into the training of the ANN, thus improving the effectiveness of the neural network greatly. Experiments results proved that this method is effective. | en |
| dc.format | 6 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Journal of WSCG. 2003, vol. 11, no. 1-3. | en |
| dc.identifier.issn | 1213-6972 | |
| dc.identifier.uri | http://wscg.zcu.cz/wscg2003/Papers_2003/D31.pdf | |
| dc.identifier.uri | http://hdl.handle.net/11025/1666 | |
| dc.language.iso | en | en |
| dc.publisher | UNION Agency – Science Press | cs |
| dc.relation.ispartofseries | Journal of WSCG | en |
| dc.rights | © UNION Agency – Science Press | cs |
| dc.rights.access | openAccess | en |
| dc.subject | detekce textu | cs |
| dc.subject | umělá neuronová síť | cs |
| dc.subject | video snímky | cs |
| dc.subject.translated | text detection | en |
| dc.subject.translated | artificial neural network | en |
| dc.subject.translated | video frames | en |
| dc.title | Automatic text detection in video frames based on bootstrap artificial neural network and CED | en |
| dc.type | článek | cs |
| dc.type | article | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |