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Segmentation of stick text based on sub connected area analysis

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Abstract

A new stick text segmentation method based on the sub connected area analysis is introduced in this paper. The foundation of this method is the sub connected area representation of text image that can represent all connected areas in an image efficiently. This method consists mainly of four steps: sub connected area classification, finding initial boundary following point, finding optimal segmentation point by boundary tracing, and text segmentation. This method is similar to boundary analysis method but is more efficient than boundary analysis.

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Authors and Affiliations

  1. CAD Center, Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, P.R. China

    Gao Jingbo, Li Xinyou & Tang Zesheng

Authors
  1. Gao Jingbo
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  2. Li Xinyou
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  3. Tang Zesheng
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Additional information

Supported by the National "863" Hi-Tech Program of China.

Gao Jingbo is a Ph.D. candidate in the Department of Computer Science and Technology, Tsinghua University. He received his B.E. degree from Tsinghua in 1993. His research area is engineering drawing recognition.

Li Xinyou is an Associate Professor in the Department of Computer Science and Technology, Tsinghua University. He received his Ph.D. degree from Tsinghua University in 1991. His research areas are engineering drawing recognition, computer graphics.

Tang Zesheng is a Professor in the Department of Computer Science and Technology, Tsinghua University. His research areas are engineering drawing recognition, computer graphics.

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Gao, J., Li, X. & Tang, Z. Segmentation of stick text based on sub connected area analysis. J. of Comput. Sci. & Technol. 13, 55–62 (1998). https://doi.org/10.1007/BF02946614

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  • DOI: https://doi.org/10.1007/BF02946614

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