Abstract
This chapter discusses video text recognition involving multiple scripts. While most video text recognition works are based on English due to much greater availability of English video datasets, there have been increasing interests in recent years in recognizing video text of other languages and scripts. In this context, this chapter first presents several language-dependent text recognition methods taking advantage of specific features of the language/script concerned, such as Chinese, Arabic/Farsi, Korean, and Indian scripts. This chapter next discusses issues in language-independent video text recognition through general text features such as edges, gradients, texture, and component connectivity while at the same time enabling detection of multi-oriented text using techniques such as Laplacian transform, Fourier transform, and gradient vector flow. Finally, this chapter examines the need for script identification for multi-script video text recognition in order to determine the appropriate OCR engine for the script identified. A method that makes use of spatial gradient feature for identification of six scripts is then described in this chapter.
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References
Liu Y, Song Y, Zhang Y, Meng Q (2013) A novel multi-oriented Chinese text extraction approach from videos. In: Proceedings of the ICDAR, pp 1355–1359
Moradi M, Mozaffari S, Oruji AA (2010) Farsi/Arabic text extraction from video images by corner detection. In: Proceedings of the MVIP, pp 1–6
Agnihotri L, Dimitrova N (1999) Text detection for video analysis. In: Proceedings of the CBAIVL, pp 109–113
Lyu MR, Song J, Cai M (2005) A comprehensive method for multilingual video text detection, localization, and extraction. IEEE Trans CSVT 15:243–255
Bhattachatya U, Parui SK, Mondal S (2009) Devanagari and Bangla text extraction from natural scene images. In: Proceedings of the ICDAR, pp 171–175
Shivakumara P, Phan TQ, Tan CL (2011) A Laplacian approach to multi-oriented text detection in video. IEEE Trans PAMI 33:412–419
Shivakumara P, Sreedhar RP, Phan TQ, Lu S, Tan CL (2012) Multi-oriented video scene text detection through Bayesian classification and boundary growing. In: Proceedings of the IEEE Trans CSVT, pp 1227–1235
Shivakumara P, Phan TQ, Lu S, Tan CL (2013) Gradient vector flow and grouping based method for arbitrarily-oriented scene text detection in video images. IEEE Trans CSVT 23:1729–1739
Basavanna M, Shivakumara P, Srivatsa SK, Hemantha Kumar G (2012) Multi-oriented text detection in scene images. Int J Pattern Recognit Artif Intell (IJPRAI) 26(7):1–19
Lucas SM, Panaretos A, Sosa L, Tang A, Wong S, Young R (2003) ICDAR 2003 robust reading competitions. InProceedings of the ICDAR, pp 1–6
Doermann D, Liang J, Li H (2003) Progress in camera-based document image analysis. In: Proceedings of the ICDAR, pp 606–616
Zang J, Kasturi R (2008) Extraction of text objects in video documents: recent progress. In: Proceedings of the DAS, pp 5–17
Jung K, Kim KI, Jain AK (2004) Text information extraction in images and video: a survey. Pattern Recognit 977–997
Ghosh D, Dube T, Shivaprasad AP (2010) Script recognition-review. IEEE Trans PAMI 32:2142–2161
Tan TN (1998) Rotation invariant texture features and their use in automatic script identification. IEEE Trans PAMI 20:751–756
Busch A, Boles WW, Sridharan S (2005) Texture for script identification. IEEE Trans PAMI 27:1720–1732
Shijian L, Tan CL (2008) Script and language identification in noisy and degraded document images. IEEE Trans PAMI 30:14–24
Jaeger S, Ma H, Doermann D (2005) Identifying script on word-level with informational confidence. In: Proceedings of the ICDAR, pp 416–420
Pati PB, Ramakrishnan AG (2008) Word level multi-script identification. Pattern Recogn Lett 1218–1229
Chanda S, Pal S, Franke K, Pal U (2009) Two-stage approach for word-wise script identification. In: Proceedings of the ICDAR, pp 926–930
Chanda S, Terrades OR, Pal U (2007) SVM based scheme for Thai and English script identification. In: Proceedings of the ICDAR, pp 551–555
Li L, Tan CL (2008) Script identification of camera-based images. In: Proceedings of the ICPR
Namboodiri AM, Jain AK (2002) on-line script recognition. In: Proceedings of the ICPR, pp 736–739
Ghosh S, Chaudhuri BB (2011) Composite script identification and orientation detection for Indian text images. In: Proceedings of the ICDAR, pp 294–298
Gllavata J, Freisleben B (2005) Script recognition in images with complex backgrounds. In: Proceedings of the IEEE international symposium on signal processing and information technology, pp 589–594
Phan TQ, Shivakumara P, Ding Z, Lu S, Tan CL (2011) Video script identification based on text lines. In: Proceedings of the ICDAR, pp 1240–1244
Sharma N, Chanda S, Pal U, Blumenstein M (2013) Word-wise script identification from video frames. In: Proceedings of the ICDAR, pp 867–871
Zhao D, Shivakumara P, Lu S, Tan CL (2012) New spatial-gradient-features for video script identification, In: Proceedings of the DAS, pp 38–42
Shivakumara P, Dutta A, Trung Quy P, Tan CL, Pal U (2011) A novel mutual nearest neighbor based symmetry for text frame classification in video. Pattern Recognit 44:1671–1683
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Lu, T., Palaiahnakote, S., Tan, C.L., Liu, W. (2014). Script Identification. In: Video Text Detection. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6515-6_8
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DOI: https://doi.org/10.1007/978-1-4471-6515-6_8
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