| Revue: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000423267 |
| ISSN: | 1405-5546 |
| Autores: | Mansouri, Sadek1 Charhad, Mbarek2 Zrigui, Mounir1 |
| Instituciones: | 1LATICE Laboratory, Research Department of Computer Science, Sfax. Túnez 2Taibah University, Almadinah Almunawwarah. Arabia Saudita |
| Año: | 2018 |
| Periodo: | Ene-Mar |
| Volumen: | 22 |
| Número: | 1 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | Automatic text detection in video sequences remains a challenging problem due to the variety of sizes, colors and the presence of complex background. In this paper, we attempt to solve this problem by proposing a robust detection-validation schema for text localization in Arabic news video. Candidate text regions are first detected by using a hybrid method which combines MSER detector and edge information. Then, these regions are grouped using morphological operators. Finally, a verification process is applied to remove noisy non-text regions including specific features for Arabic text. Performance and efficacy of the proposed text detection approach have been tested By using Arabic-Text-in-Video database (AcTiV-DB) |
| Disciplinas: | Ciencias de la computación, Literatura y lingüística |
| Palabras clave: | Lingüística aplicada, Detección automática, Textos, Arabe |
| Keyword: | Applied linguistics, Automatic detection, Texts, Arabic |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
