2018年1月25日
Detection and Recognition of Arabic Text in Video Frames
Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
- ,
- ,
- ,
- 巻
- 7
- 号
- 開始ページ
- 20
- 終了ページ
- 24
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICDAR.2017.360
- 出版者・発行元
- IEEE Computer Society
The authors have developed an end-to-end system for Arabic text recognition in video frames. The end-to-end system consists of the steps for text-line detection, word segmentation and word recognition. In order to achieve high text recognition accuracy we propose a new scheme of integrated text detection-recognition scheme, where the true text-lines are detected with as higher recall rate as possible and the false words in the false lines are rejected in the successive word recognition step. We reported a recognition based transition frame detection of Arabic news captions in single channel video images. In this paper the recognition system is integrated with n-gram language model and extended to text detection/recognition of multi-channel video images. The multi-channel, multi-font performance of the system is experimentally evaluated using AcTiV-D and AcTiV-R dataset. The multi-channel text detection performance for three channels, France24, Russia Today and TunisiaNat1 is 91.29% in (F)-measure. The multi-channel, multi-font character recognition performance for these channels is 94.84% in F-measure.
- ID情報
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- DOI : 10.1109/ICDAR.2017.360
- ISSN : 1520-5363
- SCOPUS ID : 85045270009