Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2013.122
Title: Recognition of video text through temporal integration
Authors: Phan, T.Q. 
Shivakumara, P.
Lu, T.
Tan, C.L. 
Keywords: multiple frame integration
SIFT
Stroke Width Transform
temporal integration
text binarization
text enhancement
text probability
text tracking
video text recognition
Issue Date: 2013
Citation: Phan, T.Q., Shivakumara, P., Lu, T., Tan, C.L. (2013). Recognition of video text through temporal integration. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR : 589-593. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDAR.2013.122
Abstract: This paper presents a method for temporal integration, which can be used to improve the recognition accuracy of video texts. Given a word detected in a video frame, we use a combination of Stroke Width Transform and SIFT (Scale Invariant Feature Transform) to track it both backward and forward in time. The text instances within the word's frame span are then extracted and aligned at pixel level. In the second step, we integrate these instances into a text probability map. By thresholding this map, we obtain an initial binarization of the word. In the final step, the shapes of the characters are refined using the intensity values. This helps to preserve the distinctive character features (e.g., sharp edges and holes), which are useful for OCR engines to distinguish between the different character classes. Experiments on English and German videos show that the proposed method outperforms existing ones in terms of recognition accuracy. © 2013 IEEE.
Source Title: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
URI: http://scholarbank.nus.edu.sg/handle/10635/78315
ISSN: 15205363
DOI: 10.1109/ICDAR.2013.122
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