Abstract
In this paper, we present a new optical character recognition (OCR) approach which allows real-time, automatic extraction and recognition of digits in images and videos. Our method relies on active contours in order to robustly extract optical characters from real-world visual scenes. The detected character recognition is based on template matching. Our developed system has shown excellent results when applied to the automated identification of team players׳ numbers in sport datasets and has outperformed state-of-the-art methods.
Original language | English |
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Pages (from-to) | 65-71 |
Number of pages | 7 |
Journal | Neurocomputing |
Volume | 161 |
Early online date | 9 Mar 2015 |
DOIs | |
Publication status | Published - 5 Aug 2015 |
Externally published | Yes |
Keywords
- Pattern recognition
- Information fusion
- Fast segmentation
- Scene-text localization and extraction
- Active contours
- Snake evolution