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Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel

Received: 13 May 2016     Accepted: 23 May 2016     Published: 4 June 2016
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Abstract

To solve the problem of segmenting an image into homogeneous regions with large area, this paper proposes an efficient algorithm that is based optimization base on modularity and super pixel method. Due to the fact that a very small areas of the image before segmentation, the proposed algorithm automatically merged with neighboring small areas and to make larger modules. When the modularity pictures after the merger to reach its maximum stop, leading to the production of segmentation algorithms are final. To keep repetitive patterns in a homogeneous area, a feature based on its histogram modularity with features like color and eventually identified two areas by creating a similarity matrix, it is suggested. So that the problem of segmentation and complexity of the problem to some extent eliminate in a way that due to the combined areas can be achieved for repetitive patterns. Simulation results show that the algorithm has good accuracy.

Published in Journal of Electrical and Electronic Engineering (Volume 4, Issue 3)
DOI 10.11648/j.jeee.20160403.14
Page(s) 63-67
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Segmentation, Modularity, Super Pixel

References
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[7] D. Martin, C. Fowlkes, D. Tal, and J. Malik, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics”, The Proceedings of the 8th IEEE International Conference on Computer Vision, ICCV, vol. 2, pp. 416–423, July 2001.
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Cite This Article
  • APA Style

    M. Dabbaghha, M. Dashtbayazi, S. Marjani, M. Sabaghi. (2016). Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel. Journal of Electrical and Electronic Engineering, 4(3), 63-67. https://doi.org/10.11648/j.jeee.20160403.14

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    ACS Style

    M. Dabbaghha; M. Dashtbayazi; S. Marjani; M. Sabaghi. Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel. J. Electr. Electron. Eng. 2016, 4(3), 63-67. doi: 10.11648/j.jeee.20160403.14

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    AMA Style

    M. Dabbaghha, M. Dashtbayazi, S. Marjani, M. Sabaghi. Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel. J Electr Electron Eng. 2016;4(3):63-67. doi: 10.11648/j.jeee.20160403.14

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  • @article{10.11648/j.jeee.20160403.14,
      author = {M. Dabbaghha and M. Dashtbayazi and S. Marjani and M. Sabaghi},
      title = {Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {4},
      number = {3},
      pages = {63-67},
      doi = {10.11648/j.jeee.20160403.14},
      url = {https://doi.org/10.11648/j.jeee.20160403.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20160403.14},
      abstract = {To solve the problem of segmenting an image into homogeneous regions with large area, this paper proposes an efficient algorithm that is based optimization base on modularity and super pixel method. Due to the fact that a very small areas of the image before segmentation, the proposed algorithm automatically merged with neighboring small areas and to make larger modules. When the modularity pictures after the merger to reach its maximum stop, leading to the production of segmentation algorithms are final. To keep repetitive patterns in a homogeneous area, a feature based on its histogram modularity with features like color and eventually identified two areas by creating a similarity matrix, it is suggested. So that the problem of segmentation and complexity of the problem to some extent eliminate in a way that due to the combined areas can be achieved for repetitive patterns. Simulation results show that the algorithm has good accuracy.},
     year = {2016}
    }
    

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    AU  - M. Dashtbayazi
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    AB  - To solve the problem of segmenting an image into homogeneous regions with large area, this paper proposes an efficient algorithm that is based optimization base on modularity and super pixel method. Due to the fact that a very small areas of the image before segmentation, the proposed algorithm automatically merged with neighboring small areas and to make larger modules. When the modularity pictures after the merger to reach its maximum stop, leading to the production of segmentation algorithms are final. To keep repetitive patterns in a homogeneous area, a feature based on its histogram modularity with features like color and eventually identified two areas by creating a similarity matrix, it is suggested. So that the problem of segmentation and complexity of the problem to some extent eliminate in a way that due to the combined areas can be achieved for repetitive patterns. Simulation results show that the algorithm has good accuracy.
    VL  - 4
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Author Information
  • Department of Telecommunications and Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran

  • Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

  • Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

  • Laser and Optics Research School, Nuclear Science and Technology Research Institute (NSTRI), Tehran, Iran

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