| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 484831 | Procedia Computer Science | 2015 | 8 Pages |
Text detection is a basic step in many computer vision applications including video Optical Character Recognition (OCR), video indexation, understanding video content, etc. Actually, several sources such as mobile devices, monitoring cameras and social networks are generating every day billions of videos with different formats and uncertainty. Such videos require new methods to apply text detection. In this paper, we are introducing a novel text detection technique using many blocks coming from frame decomposition. Each block is analyzed and classified which allowed the extraction of text coordinates using MapReduce programming model. To validate our approach, we test it on YouTube Video Text (YVT) dataset and we found that the running speed of this approach can be more than 2 times as fast as classic approach.
