NDLI: Recognition of Video Text through Temporal Integration

Content Provider	IEEE Xplore Digital Library
Author	Phan, T.Q. Shivakumara, P. Tong Lu Tan, C.L.
Copyright Year	2013
Description	Author affiliation: Nat. Key Lab. of Novel Software Technol., Nanjing Univ., Nanjing, China (Tong Lu) \|\| Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore (Phan, T.Q.; Tan, C.L.) \|\| Fac. of Comput. Sci. & Inf. Technol., Univ. of Malaya, Kuala Lumpur, Malaysia (Shivakumara, P.)
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.
Starting Page	589
Ending Page	593
File Size	278163
Page Count	5
File Format	PDF
ISBN	9780769549996
ISSN	15205363
DOI	10.1109/ICDAR.2013.122
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Text recognition Shape Optical character recognition software Engines Accuracy Feature extraction Character recognition text probability video text recognition multiple frame integration temporal integration text tracking text enhancement text binarization Stroke Width Transform SIFT
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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