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Text Segmentation in Complex Background Based on Color and Scale Information of Character Strokes

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Advances in Multimedia Information Processing – PCM 2007 (PCM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4810))

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Abstract

This paper presents a robust approach to segmenting text embedded in complex background. Our approach consists of four steps: smart sampling, unsupervised clustering, the Bayesian decision, post-processing. The experimental results show that it works effectively, and is more efficient in removing complex background residues than the popular K-means method.

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Authors and Affiliations

  1. Institute of Computing Technology, CAS, Beijing, 100080, China

    Weiqiang Wang, Libo Fu & Wen Gao

  2. Graduate School of Chinese Academy of Sciences, CAS, Beijing, 100039, China

    Weiqiang Wang & Wen Gao

Authors
  1. Weiqiang Wang
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  2. Libo Fu
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  3. Wen Gao
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Editor information

Horace H.-S. Ip Oscar C. Au Howard Leung Ming-Ting Sun Wei-Ying Ma Shi-Min Hu

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© 2007 Springer-Verlag Berlin Heidelberg

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Wang, W., Fu, L., Gao, W. (2007). Text Segmentation in Complex Background Based on Color and Scale Information of Character Strokes. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_44

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  • DOI: https://doi.org/10.1007/978-3-540-77255-2_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77254-5

  • Online ISBN: 978-3-540-77255-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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