Name
Abstract | ||
|---|---|---|
Video text usually provides us a lot of useful information that is important for video analysis, indexing and retrieval. However, it is still a challenging work to detect text from video images due to variation of text patterns and complexity of background. In this paper, an automatic video text detection method is proposed. Firstly, K-means is utilized to classify pixels in gradient images into text and non-text regions. Subsequently, morphological operations are performed on text regions to form connected candidate text components, followed by projection profile boundary refinement. Finally, the detection results are verified by geometry and BP-Adaboost identifications. The experimental results on our manually selected dataset and the publicly available Microsoft Asia dataset show the effectiveness and feasibility of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s11042-015-2690-6 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Video text detection,Morphological operations,Projection profile,BP-Adaboost | Computer vision,AdaBoost,Pattern recognition,Computer science,Search engine indexing,Video tracking,Artificial intelligence,Pixel,Text detection | Journal |
Volume | Issue | ISSN |
75 | 13 | 1380-7501 |
Citations | PageRank | References |
1 | 0.35 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| hui wu | 1 | 5 | 0.73 |
| Beiji Zou | 2 | 231 | 41.61 |
| Yu-Qian Zhao | 3 | 92 | 9.98 |
| hongpu fu | 4 | 1 | 0.35 |