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Detecting both superimposed and scene text with multiple languages and multiple alignments in video

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Abstract

Video text often contains highly useful semantic information that can contribute significantly to video retrieval and understanding. Video text can be classified into scene text and superimposed text. Most of the previous methods detect superimposed or scene text separately due to different text alignments. Moreover, because different language characters have different edge and texture features, it is very difficult to detect the multilingual text. In this paper, we first perform a detailed analysis of motion patterns of video text, and show that the superimposed and scene text exhibit different motion patterns on consecutive frames, which is insensitive to multiple language characters and multiple text alignments. Based on our analysis, we define Motion Perception Field (MPF) to represent the text motion patterns. Finally, we propose a text detection algorithms using MPF for both superimposed and scene text with multiple languages and multiple alignments. Experimental results on diverse videos demonstrate that our algorithms are robust, and outperform previous methods for detecting both superimposed and scene texts with multiple languages and multiple alignments.

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Notes

  1. China Central Television, or CCTV, is a national television station of the People’s Republic of China. It was on its trial broadcast on May 1st, 1958, and formally launched on September 2nd of the year. As the most important medium in China, CCTV not only provides information to general public throughout China, but also works as an open window between China and the rest of the world.

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Acknowledgment

The authors would like to thank the reviewers for their thorough comments and suggestions that helped to improve this paper. This work is supported by the National Natural Science Foundation for Distinguished Young Scholars under Grant No. 60925010; the National Natural Science Foundation of China under Grant No. 60833009; the Cosponsored Project of Beijing Committee of Education, the Funds for Creative Research Groups of China under Grant No.61121001, and the Program for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT1049.

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Authors and Affiliations

  1. Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Xiaodong Huang, Huadong Ma, Charles X. Ling & Guangyu Gao

  2. Capital Normal University, Beijing, 100048, China

    Xiaodong Huang

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  1. Xiaodong Huang
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  2. Huadong Ma
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  3. Charles X. Ling
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  4. Guangyu Gao
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Correspondence to Huadong Ma.

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Huang, X., Ma, H., Ling, C.X. et al. Detecting both superimposed and scene text with multiple languages and multiple alignments in video. Multimed Tools Appl 70, 1703–1727 (2014). https://doi.org/10.1007/s11042-012-1201-2

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