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An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique

When analysing objects in images, it is necessary to distinguish the objects of interest from the background. This task can be achieved through segmentation process. Image segmentation is one of the most challenging issues in image processing domain. It remains an active research area with aims to d...

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Main Authors: Lahani, J, Sulaiman, H. A, Muniandy, R. K, Bade, A
Format: Article
Language:English
Published: 2018
Subjects:
QC Physics
Online Access:https://eprints.ums.edu.my/id/eprint/23692/1/An%20Enhanced%20Edge%20Detection%20Method%20Based%20on%20Integration%20of%20Entropy.pdf
https://eprints.ums.edu.my/id/eprint/23692/
https://doi.org/10.1166/asl.2018.11112
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spelling my.ums.eprints.236922019-09-30T00:26:28Z https://eprints.ums.edu.my/id/eprint/23692/ An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique Lahani, J Sulaiman, H. A Muniandy, R. K Bade, A QC Physics When analysing objects in images, it is necessary to distinguish the objects of interest from the background. This task can be achieved through segmentation process. Image segmentation is one of the most challenging issues in image processing domain. It remains an active research area with aims to distinguish between the foreground and background of objects. In order to extract the useful information from an image, edge detection is a reliable technique to solve this issue. Edge detection is a technique that aims at extracting the boundaries of the image by manipulating discontinuities gaps between pixels. This paper focuses on demonstrating an enhanced integrating framework; a modified entropy based approach with an enhanced Canny technique. By integrating two well-known techniques, the true edges were able to identify effectively. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) for the proposed technique shown was 4.1% and 16.75% higher than prominent techniques respectively. The proposed technique produced better similarity quality image and contains lesser noise. 2018-03 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/23692/1/An%20Enhanced%20Edge%20Detection%20Method%20Based%20on%20Integration%20of%20Entropy.pdf Lahani, J and Sulaiman, H. A and Muniandy, R. K and Bade, A (2018) An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique. American Scientific Publishers, 24 (3). pp. 1575-1578. https://doi.org/10.1166/asl.2018.11112
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic QC Physics
spellingShingle QC Physics
Lahani, J
Sulaiman, H. A
Muniandy, R. K
Bade, A
An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
description When analysing objects in images, it is necessary to distinguish the objects of interest from the background. This task can be achieved through segmentation process. Image segmentation is one of the most challenging issues in image processing domain. It remains an active research area with aims to distinguish between the foreground and background of objects. In order to extract the useful information from an image, edge detection is a reliable technique to solve this issue. Edge detection is a technique that aims at extracting the boundaries of the image by manipulating discontinuities gaps between pixels. This paper focuses on demonstrating an enhanced integrating framework; a modified entropy based approach with an enhanced Canny technique. By integrating two well-known techniques, the true edges were able to identify effectively. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) for the proposed technique shown was 4.1% and 16.75% higher than prominent techniques respectively. The proposed technique produced better similarity quality image and contains lesser noise.
format Article
author Lahani, J
Sulaiman, H. A
Muniandy, R. K
Bade, A
author_facet Lahani, J
Sulaiman, H. A
Muniandy, R. K
Bade, A
author_sort Lahani, J
title An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
title_short An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
title_full An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
title_fullStr An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
title_full_unstemmed An Enhanced Edge Detection Method Based on Integration of Entropy—Canny Technique
title_sort enhanced edge detection method based on integration of entropy—canny technique
publishDate 2018
url https://eprints.ums.edu.my/id/eprint/23692/1/An%20Enhanced%20Edge%20Detection%20Method%20Based%20on%20Integration%20of%20Entropy.pdf
https://eprints.ums.edu.my/id/eprint/23692/
https://doi.org/10.1166/asl.2018.11112
_version_ 1760230141605183488
score 13.211869

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