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Introduction to Video Text Detection

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Video Text Detection

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Text plays a dominant role in video viewing and understanding as text carries rich and important information relevant to the video contents. Studies have shown that humans often pay first attention to text over other objects in a video as text helps in getting semantics relevant to the content of the video. With this in mind, this chapter introduces research in video text detection. It first reviews relevant literature and then discusses characteristics and difficulties of video text detection faced by the majority of the methods under review. Various issues such as low resolution of video images, the presence of both caption and scene text in video, and background complexity variations are examined. This chapter also presents a brief historical overview to show how video text detection has evolved from the field of document image analysis and how the document analysis community has explored various methods proposed in different fields, including image processing, pattern recognition, computer vision, and artificial intelligence to find solution to text detection in video. Finally, this chapter discusses potential applications of video text detection.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Nanjing University, Nanjing, China

    Tong Lu

  2. Faculty of CSIT, University of Malaya, Kuala Lumpur, Malaysia

    Shivakumara Palaiahnakote

  3. National University of Singapore, Singapore, Singapore

    Chew Lim Tan

  4. Multimedia Software Engineering Research Center, City University of Hong Kong, Kowloon Tong, Hong Kong SAR

    Wenyin Liu

Authors
  1. Tong Lu
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  2. Shivakumara Palaiahnakote
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  3. Chew Lim Tan
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  4. Wenyin Liu
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© 2014 Springer-Verlag London

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Lu, T., Palaiahnakote, S., Tan, C.L., Liu, W. (2014). Introduction to Video Text Detection. In: Video Text Detection. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6515-6_1

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  • DOI: https://doi.org/10.1007/978-1-4471-6515-6_1

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6514-9

  • Online ISBN: 978-1-4471-6515-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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