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Detection of Text Region and Segmentation from Natural Scene Images

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Advances in Visual Computing (ISVC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3804))

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Abstract

In this paper, we present an approach to the segmentation and detection of text region from natural scenes. Clustering-based natural scene segmentation is first considered based on the histogram of hue and intensity components separately. Secondly, text region extraction method is proposed by using wavelet-based features for representing the input patterns and neural network architecture for the classifier. The effectiveness and reliability of the proposed method is demonstrated through various natural scene images. The experimental results have proven that the proposed method is effective.

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Author information

Authors and Affiliations

  1. Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, California, 90089-0273

    Jonghyun Park

  2. Dept. of Electronic Engineering, Mokpo National University, South Korea

    Soonyoung Park

Authors
  1. Jonghyun Park
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  2. Soonyoung Park
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  4. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

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© 2005 Springer-Verlag Berlin Heidelberg

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Park, J., Park, S. (2005). Detection of Text Region and Segmentation from Natural Scene Images. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_83

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  • DOI: https://doi.org/10.1007/11595755_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30750-1

  • Online ISBN: 978-3-540-32284-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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