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The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition

Edge detection is important in image analysis to form the shape of an object.Edge is the boundary between different textures, which helps with object segmentation and recognition.Currently, several edge detection techniques are able to identify objects but are unable to localize the shape of an obje...

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Main Authors: Othman, Mahmod, Syed Abdullah, Sharifah Lailee, Ahmad, Khairul Adilah, Abu Bakar, Mohd Nazari, Mansor, Ab Razak
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2016
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/24076/1/JICT%2015%201%202016%20%20133%E2%80%93144.pdf
http://repo.uum.edu.my/24076/
http://jict.uum.edu.my/index.php/previous-issues/148-journal-of-information-and-communication-technology-jict-vol-15-no1-june-2016
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spelling my.uum.repo.240762020-11-01T08:18:31Z http://repo.uum.edu.my/24076/ The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition Othman, Mahmod Syed Abdullah, Sharifah Lailee Ahmad, Khairul Adilah Abu Bakar, Mohd Nazari Mansor, Ab Razak QA75 Electronic computers. Computer science Edge detection is important in image analysis to form the shape of an object.Edge is the boundary between different textures, which helps with object segmentation and recognition.Currently, several edge detection techniques are able to identify objects but are unable to localize the shape of an object. To address this problem, this paper proposes a fusion of selected edge detection algorithms with mathematical morphology to enhance the ability to detect the object shape boundary. Edge detection algorithm is used to simplify image data by minimizing the amount of pixel to be processed, whereas the mathematical morphology is used for smoothing effects and localizing the object shape using mathematical theory sets.The discussion section focuses on the improved edge map and boundary morphology (EmaBm) algorithm as a new technique for shape boundary recognition.A comparative analysis of various edge detection algorithms is presented.It reveals that the LoG’s edge detection embedded in EmaBM algorithm performs better than the other edge detection algorithms for fruit shape boundary recognition. Implementation of the proposed method shows that it is robust and applicable for various kind of fruit images and is more accurate than the existing edge detection algorithms. Universiti Utara Malaysia Press 2016 Article PeerReviewed application/pdf en http://repo.uum.edu.my/24076/1/JICT%2015%201%202016%20%20133%E2%80%93144.pdf Othman, Mahmod and Syed Abdullah, Sharifah Lailee and Ahmad, Khairul Adilah and Abu Bakar, Mohd Nazari and Mansor, Ab Razak (2016) The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition. Journal of Information and Communication Technology, 15 (1). pp. 133-144. ISSN 2180-3862 http://jict.uum.edu.my/index.php/previous-issues/148-journal-of-information-and-communication-technology-jict-vol-15-no1-june-2016
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Othman, Mahmod
Syed Abdullah, Sharifah Lailee
Ahmad, Khairul Adilah
Abu Bakar, Mohd Nazari
Mansor, Ab Razak
The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
description Edge detection is important in image analysis to form the shape of an object.Edge is the boundary between different textures, which helps with object segmentation and recognition.Currently, several edge detection techniques are able to identify objects but are unable to localize the shape of an object. To address this problem, this paper proposes a fusion of selected edge detection algorithms with mathematical morphology to enhance the ability to detect the object shape boundary. Edge detection algorithm is used to simplify image data by minimizing the amount of pixel to be processed, whereas the mathematical morphology is used for smoothing effects and localizing the object shape using mathematical theory sets.The discussion section focuses on the improved edge map and boundary morphology (EmaBm) algorithm as a new technique for shape boundary recognition.A comparative analysis of various edge detection algorithms is presented.It reveals that the LoG’s edge detection embedded in EmaBM algorithm performs better than the other edge detection algorithms for fruit shape boundary recognition. Implementation of the proposed method shows that it is robust and applicable for various kind of fruit images and is more accurate than the existing edge detection algorithms.
format Article
author Othman, Mahmod
Syed Abdullah, Sharifah Lailee
Ahmad, Khairul Adilah
Abu Bakar, Mohd Nazari
Mansor, Ab Razak
author_facet Othman, Mahmod
Syed Abdullah, Sharifah Lailee
Ahmad, Khairul Adilah
Abu Bakar, Mohd Nazari
Mansor, Ab Razak
author_sort Othman, Mahmod
title The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
title_short The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
title_full The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
title_fullStr The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
title_full_unstemmed The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
title_sort fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
publisher Universiti Utara Malaysia Press
publishDate 2016
url http://repo.uum.edu.my/24076/1/JICT%2015%201%202016%20%20133%E2%80%93144.pdf
http://repo.uum.edu.my/24076/
http://jict.uum.edu.my/index.php/previous-issues/148-journal-of-information-and-communication-technology-jict-vol-15-no1-june-2016
_version_ 1683233078357524480
score 13.23648

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