Abstract
In this paper, we present a new optical character recognition approach. Our method combines chromaticitybased character detection with active contour segmentation in order to robustly extract optical characters form real-world images and videos. The detected character is recognized using template matching. Our developed approach has shown excellent results when applied to the automatic identification of team players from online datasets and is more efficient than the state-of-the-art methods.
| Original language | English |
|---|---|
| Title of host publication | BIOSIGNALS 2014 7th International Conference on Bio-Inspired Systems and Signal Processing |
| Subtitle of host publication | Angers, France |
| Editors | Harald Loose, Guy Plantier, Tanja Schultz, Ana Fred, Hugo Gamboa |
| Publisher | SciTePress |
| Pages | 318-324 |
| Number of pages | 7 |
| Volume | 1 |
| ISBN (Electronic) | 9789897580116 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
Keywords
- Active contours
- Multi-feature vector flow
- Tracking
- Optical character recognition
- Pattern recognition
- Unsupervised segmentation
- Object detection
- Team sport video analysis
- Automated scene understanding