TextFinder: An Automatic System to Detect and Recognize Text In Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic location of text in video frames
MULTIMEDIA '01 Proceedings of the 2001 ACM workshops on Multimedia: multimedia information retrieval
Automatic News Video Caption Extraction and Recognition
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Improving the Spatial-Temporal Clue Based Segmentation by the Use of Rhythm
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Text Detection for Video Analysis
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
Text detection and segmentation in complex color images
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
An Interactive Device for Quick Arabic News Story Browsing
International Journal of Mobile Computing and Multimedia Communications
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With the rapid growth of the number of TV channels, the internet and online information services, more and more information becomes available and accessible. The digitization enhances preservation of records and makes the access to documents easier. However, when the quantity of documents become important the digitalization is not enough to ensure an efficient access. Indeed, we need to extract semantic information to help users to find what we need quickly. The text included in video sequences is highly needed for indexing and searching system. However, this text is difficult to detect and recognize because of the variability of its size, low resolution characters and the complexity of the backgrounds. To resolve these shortcomings, we propose a two task system: As a first step, we extract the textual information from video sequences and second, we recognize this text. Our system is tested on a diverse database composed of several Arabic news broadcast. The obtained results are encouraging and prove the qualities of our approach.