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An Algorithm for Colour-Based Natural Scene Text Segmentation

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7139)

Abstract

Before the step for text recognition, a text image needs to be segmented into foreground containing only the text area and background. In this paper, a method is proposed for segmenting colour natural scene texts which suffer from a wide range of degradations with complex background. A text image is firstly processed by two 3-means clustering operations with different distance measurements. Then, a modified connected component (CC)-based validation method is used to obtain the text area after clustering. Thirdly, a proposed objective segmentation evaluation method is utilised to choose the final segmentation result from the two segmented text images. The proposed method is compared with other existing methods based on the ICDAR2003 public database. Experimental results show the effectiveness of the proposed method.

Keywords

  • natural scene text segmentation
  • k-means clustering
  • connected component analysis (CCA)
  • segmentation evaluation

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© 2012 Springer-Verlag Berlin Heidelberg

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Zeng, C., Jia, W., He, X. (2012). An Algorithm for Colour-Based Natural Scene Text Segmentation. In: Iwamura, M., Shafait, F. (eds) Camera-Based Document Analysis and Recognition. CBDAR 2011. Lecture Notes in Computer Science, vol 7139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29364-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-29364-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29363-4

  • Online ISBN: 978-3-642-29364-1

  • eBook Packages: Computer ScienceComputer Science (R0)