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

M. Dabbaghha; M. Dashtbayazi; S. Marjani; M. Sabaghi

doi:doi:10.11648/j.jeee.20160403.14

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

M. Dabbaghha, M. Dashtbayazi, S. Marjani, M. Sabaghi

Published in Journal of Electrical and Electronic Engineering (Volume 4, Issue 3)

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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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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TY - JOUR
T1 - Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel
AU - M. Dabbaghha
AU - M. Dashtbayazi
AU - S. Marjani
AU - M. Sabaghi
Y1 - 2016/06/04
PY - 2016
N1 - https://doi.org/10.11648/j.jeee.20160403.14
DO - 10.11648/j.jeee.20160403.14
T2 - Journal of Electrical and Electronic Engineering
JF - Journal of Electrical and Electronic Engineering
JO - Journal of Electrical and Electronic Engineering
SP - 63
EP - 67
PB - Science Publishing Group
SN - 2329-1605
UR - https://doi.org/10.11648/j.jeee.20160403.14
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
IS - 3
ER -

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Author Information

M. Dabbaghha

Department of Telecommunications and Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran
M. Dashtbayazi

Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
S. Marjani

Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
M. Sabaghi

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

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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}
}

Copy | Download