Edge Detection of an Image Based on Extended Difference of Gaussian

Hameda Abd El-Fattah El-Sennary; Mohamed Eid Hussien; Abd El-Mgeid Amin Ali

doi:doi:10.11648/j.ajcst.20190203.11

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Edge Detection of an Image Based on Extended Difference of Gaussian

Hameda Abd El-Fattah El-Sennary, Mohamed Eid Hussien, Abd El-Mgeid Amin Ali

Published in American Journal of Computer Science and Technology (Volume 2, Issue 3)

Received: 24 November 2019 Accepted: 9 December 2019 Published: 20 December 2019

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Abstract

Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.

Published in	American Journal of Computer Science and Technology (Volume 2, Issue 3)
DOI	10.11648/j.ajcst.20190203.11
Page(s)	35-47
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), 2019. Published by Science Publishing Group

Keywords

Edge Detection, Image Quality, Gaussian Filter, Extended Difference of Gaussian, Peak Signal to Ratio, Mean Square Error

References

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APA Style

Hameda Abd El-Fattah El-Sennary, Mohamed Eid Hussien, Abd El-Mgeid Amin Ali. (2019). Edge Detection of an Image Based on Extended Difference of Gaussian. American Journal of Computer Science and Technology, 2(3), 35-47. https://doi.org/10.11648/j.ajcst.20190203.11

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ACS Style

Hameda Abd El-Fattah El-Sennary; Mohamed Eid Hussien; Abd El-Mgeid Amin Ali. Edge Detection of an Image Based on Extended Difference of Gaussian. Am. J. Comput. Sci. Technol. 2019, 2(3), 35-47. doi: 10.11648/j.ajcst.20190203.11

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AMA Style

Hameda Abd El-Fattah El-Sennary, Mohamed Eid Hussien, Abd El-Mgeid Amin Ali. Edge Detection of an Image Based on Extended Difference of Gaussian. Am J Comput Sci Technol. 2019;2(3):35-47. doi: 10.11648/j.ajcst.20190203.11

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@article{10.11648/j.ajcst.20190203.11,
  author = {Hameda Abd El-Fattah El-Sennary and Mohamed Eid Hussien and Abd El-Mgeid Amin Ali},
  title = {Edge Detection of an Image Based on Extended Difference of Gaussian},
  journal = {American Journal of Computer Science and Technology},
  volume = {2},
  number = {3},
  pages = {35-47},
  doi = {10.11648/j.ajcst.20190203.11},
  url = {https://doi.org/10.11648/j.ajcst.20190203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20190203.11},
  abstract = {Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.},
 year = {2019}
}

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TY  - JOUR
T1  - Edge Detection of an Image Based on Extended Difference of Gaussian
AU  - Hameda Abd El-Fattah El-Sennary
AU  - Mohamed Eid Hussien
AU  - Abd El-Mgeid Amin Ali
Y1  - 2019/12/20
PY  - 2019
N1  - https://doi.org/10.11648/j.ajcst.20190203.11
DO  - 10.11648/j.ajcst.20190203.11
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 35
EP  - 47
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20190203.11
AB  - Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.
VL  - 2
IS  - 3
ER  -

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Author Information

Hameda Abd El-Fattah El-Sennary

Faculty of Science, Aswan University, Aswan, Egypt
Mohamed Eid Hussien

Faculty of Science, Aswan University, Aswan, Egypt
Abd El-Mgeid Amin Ali

Faculty of Computers and Information, Minia University, Minia, Egypt

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Plain Text BibTeX RIS

APA Style

Hameda Abd El-Fattah El-Sennary, Mohamed Eid Hussien, Abd El-Mgeid Amin Ali. (2019). Edge Detection of an Image Based on Extended Difference of Gaussian. American Journal of Computer Science and Technology, 2(3), 35-47. https://doi.org/10.11648/j.ajcst.20190203.11

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ACS Style

Hameda Abd El-Fattah El-Sennary; Mohamed Eid Hussien; Abd El-Mgeid Amin Ali. Edge Detection of an Image Based on Extended Difference of Gaussian. Am. J. Comput. Sci. Technol. 2019, 2(3), 35-47. doi: 10.11648/j.ajcst.20190203.11

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AMA Style

Hameda Abd El-Fattah El-Sennary, Mohamed Eid Hussien, Abd El-Mgeid Amin Ali. Edge Detection of an Image Based on Extended Difference of Gaussian. Am J Comput Sci Technol. 2019;2(3):35-47. doi: 10.11648/j.ajcst.20190203.11

Copy | Download

@article{10.11648/j.ajcst.20190203.11,
  author = {Hameda Abd El-Fattah El-Sennary and Mohamed Eid Hussien and Abd El-Mgeid Amin Ali},
  title = {Edge Detection of an Image Based on Extended Difference of Gaussian},
  journal = {American Journal of Computer Science and Technology},
  volume = {2},
  number = {3},
  pages = {35-47},
  doi = {10.11648/j.ajcst.20190203.11},
  url = {https://doi.org/10.11648/j.ajcst.20190203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20190203.11},
  abstract = {Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Edge Detection of an Image Based on Extended Difference of Gaussian
AU  - Hameda Abd El-Fattah El-Sennary
AU  - Mohamed Eid Hussien
AU  - Abd El-Mgeid Amin Ali
Y1  - 2019/12/20
PY  - 2019
N1  - https://doi.org/10.11648/j.ajcst.20190203.11
DO  - 10.11648/j.ajcst.20190203.11
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 35
EP  - 47
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20190203.11
AB  - Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.
VL  - 2
IS  - 3
ER  -

Copy | Download