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Adaptive Heuristic Colorful Text Image Segmentation Using Soft Computing, Enhanced Density-Based Scan Algorithm and HSV Color Model

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New Research in Multimedia and Internet Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 314))

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Abstract

This chapter describes intelligent multilayer image segmentation algorithm for Optical Character Recognition system. The additional algorithm brings new ability of recognizing colorful texts. Presented solution allows to successfully recognize texts with various background and foreground colors even when their luminosity values are equal. It may be adapted into current OCR systems or work as a standalone pre-processing system.

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References

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Author information

Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, ul. Wólczańska 215, 90-924, Łódź, Poland

    Adam Musiał

Authors
  1. Adam Musiał
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Corresponding author

Correspondence to Adam Musiał .

Editor information

Editors and Affiliations

  1. Division of Information Systems, Wroclaw University of Technology Institute of Informatics, Wrocław, Poland

    Aleksander Zgrzywa

  2. Division of Information Systems Institute of Informatics, Wroclaw University of Technology, Wrocław, Poland

    Kazimierz Choroś

  3. Division of Information Systems Institute of Informatics, Wroclaw University of Technology, Wrocław, Poland

    Andrzej Siemiński

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Musiał, A. (2015). Adaptive Heuristic Colorful Text Image Segmentation Using Soft Computing, Enhanced Density-Based Scan Algorithm and HSV Color Model. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) New Research in Multimedia and Internet Systems. Advances in Intelligent Systems and Computing, vol 314. Springer, Cham. https://doi.org/10.1007/978-3-319-10383-9_15

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  • DOI: https://doi.org/10.1007/978-3-319-10383-9_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10382-2

  • Online ISBN: 978-3-319-10383-9

  • eBook Packages: EngineeringEngineering (R0)

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