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Color Texture Image Segmentation Based on Neutrosophic Set and Nonsubsampled Contourlet Transformation

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Applied Algorithms (ICAA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8321))

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Abstract

In this paper, an automatic approach for image segmentation based on neutrosophic set and nonsubsampled contourlet transformation for natural images is proposed. This method uses both color and texture features for segmentation. Input image is transformed into LUV color model for extracting the color features. Texture features are extracted from the grayscale image. Image is then transformed into Neutrosophic domain. Finally, image segmentation is performed using Fuzzy C-means clustering. Clusters are adaptively calculated based on a cluster validity analysis. This method is tested in natural image database. The result analysis shows that the proposed method automatically segments image better than traditional methods.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India

    Jeethu Mary Mathew & Philomina Simon

Authors
  1. Jeethu Mary Mathew
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  2. Philomina Simon
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Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Heritage Institute of Technology, Chowbaga Road, Anandapur, 700107, Kolkata, India

    Prosenjit Gupta

  2. Department of Computer Engineering and Informatics, University of Patras, 26500, Patras, Greece

    Christos Zaroliagis

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© 2014 Springer International Publishing Switzerland

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Mathew, J.M., Simon, P. (2014). Color Texture Image Segmentation Based on Neutrosophic Set and Nonsubsampled Contourlet Transformation. In: Gupta, P., Zaroliagis, C. (eds) Applied Algorithms. ICAA 2014. Lecture Notes in Computer Science, vol 8321. Springer, Cham. https://doi.org/10.1007/978-3-319-04126-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-04126-1_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04125-4

  • Online ISBN: 978-3-319-04126-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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