Video-Tag Detection and Recognition

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Abstract:

In this work, we present a video-tag detection and recognition method. According to the duration of the video, choose an appropriate strategy to sample the frames. After the candidate tag of every frame is computed, a median filter algorithm is employed to get the tag boundary. At last the binary video-tag is determined by a multi-frame-based analysis algorithm. After scaling the binary tag image to the standard size, a full image-matching algorithm is used to recognize the tag. The experimental results indicate the proposed video-tag detection method has high recall ratio and precision ratio, and the image-matching-based video-tag recognition method performs much better than the traditional OCR methods.

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2528-2533

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June 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] R Lienhart , A Wernicke. Localizing and segmenting text in images, videos. IEEE Transactions on Circuits Syst Video Technol, 2002, 12 (4): 256-268.

DOI: 10.1109/76.999203

Google Scholar

[2] Palaiahnakote Shivakumara, Weihua Huang, Chew Lim Tan. Efficient Video Text Detection using Edge Features. Proceedings of the 19th International Conference on Pattern Recognition, Tampa , USA : IEEE Computer Society, 2008: 1-4.

DOI: 10.1109/icpr.2008.4761417

Google Scholar

[3] Trung Quy Phan, Palaiahnakote Shivakumara and Chew Lim Tan. A Laplacian Method for Video Text Detection. Proceedings of the 10th International Conference on Document Analysis and Recognition. Barcelona, Spain , IEEE Computer Society, 2009: 66-70.

DOI: 10.1109/icdar.2009.153

Google Scholar

[4] K Jain , B Yu. Automatic text location in images and video frames . Pattern Recognition , 1998, 31(12) : 2055-(2076).

DOI: 10.1016/s0031-3203(98)00067-3

Google Scholar

[5] CHENG Hao, HUANG Lei, LIU Jin-gang. Video Text Segmentation Algorithm Based on Stroke Extraction and Color Model. Computer Engineering, 2009, 35(4) : 193-195.

Google Scholar

[6] Wenge Mao , Fu2lai Chung , Lam , K K M , Wan2chi Sun. Hybrid Chinese/ English text detection in images and video frames . Proceedings of 16th International Conference on Pattern Recognition , 2002 . Washington , DC , USA : IEEE Computer Society, 2002: 1015-1018.

DOI: 10.1109/icpr.2002.1048210

Google Scholar

[7] J Gllavata , R Ewerth , B Freisleben. A text detection , localization and segmentation system for OCR in images . Proceedings of the IEEE Sixth International Symposium on Multimedia Software Engineering[C] . Washington , DC , USA : IEEE Computer Society , 2004.: 310 - 317.

DOI: 10.1109/mmse.2004.18

Google Scholar

[8] TIAN Po-huang , PENG Tian-qiang , LI Bi-cheng . An Approach for Video-text Extraction Based on Text Traversing Line and Stroke Connectivity. ACTA ELECTRONICA SINICA, 2009, 37(1), 72-78.

DOI: 10.1109/icosp.2008.4697297

Google Scholar

[9] R Lienhart , A Wernicke1 Localizing and segmenting text in images and videos. IEEE Trans on Circuits and System for Video Technology, 2002 , 12 (4) : 256-268.

DOI: 10.1109/76.999203

Google Scholar

[10] H Li , D Doermann , O Kia1 Automatic text detection and tracking in digital video. IEEE Trans on Image Processing , 2000 , 9 (1) : 147-156.

DOI: 10.1109/83.817607

Google Scholar

[11] Mi Congjie , Liu Yang , and Xue Xiangyang. Video Texts Tracking and Segmentation Based on Multiple Frames. Journal of Computer Research and Development, 2006, 43 (9) : 1523-1529.

DOI: 10.1360/crad20060906

Google Scholar

[12] LI Zhaohui, WANG Xiufeng. Research on Caption of Film Character Recognition. Computer Engineering, 2002, 28(3): 175-176.

Google Scholar

[13] Datong Chen, Jean-Marc Odobez, Herve Bourlard. Text detection and recognition in images and video frames[J]. Pattern Recognition, 2004, 37, 595-608.

DOI: 10.1016/j.patcog.2003.06.001

Google Scholar

[14] Ohkura, A, Deguchi, D, Takahashi,T. Low-Resolution Character Recognition by Video-Based Super-Resolution. Proceedings of the 10th International Conference on Document Analysis and Recognition, Barcelona, Spain: IEEE Computer Society , 2009: 191-195.

DOI: 10.1109/icdar.2009.168

Google Scholar