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An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization

Breast cancer is one the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the computation methods have greater accurate diagnosis ability. An enhancement of multi classifiers voting technique based on histogram equalization as a...

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Main Authors: Ibrahim, Ashraf Osman, Ahmed, Ali, Azizah, Anik Hanifatul, Lashar, Saima Anwar, Alobeed, Mohamed Alhaj, Kasim, Shahreen, Ismail, Mohd Arfian
Format: Article
Language:English
Published: Penerbit UTHM 2018
Subjects:
TR624-835 Applied photography. Including artistic, commercial, medical photography, photocopying processes
Online Access:http://eprints.uthm.edu.my/3661/1/AJ%202018%20%28712%29%20An%20enhancement%20of%20multi%20classifiers%20voting%20method%20for%20mammogram%20image%20based%20on%20image%20histogram%20equalization.pdf
http://eprints.uthm.edu.my/3661/
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spelling my.uthm.eprints.36612021-11-21T06:33:02Z http://eprints.uthm.edu.my/3661/ An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization Ibrahim, Ashraf Osman Ahmed, Ali Azizah, Anik Hanifatul Lashar, Saima Anwar Alobeed, Mohamed Alhaj Kasim, Shahreen Ismail, Mohd Arfian TR624-835 Applied photography. Including artistic, commercial, medical photography, photocopying processes Breast cancer is one the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the computation methods have greater accurate diagnosis ability. An enhancement of multi classifiers voting technique based on histogram equalization as a preprocessing stage proposed in this paper. The methodology is based on five phases starting by mammogram images collection, preprocessing (histogram equalization and image cropping based region of interest (ROI)), features extracting, classification and last evaluating the classification results. An experimental conducted on different training-testing partitions of the dataset. The numerical results demonstrate that the proposed scheme achieves an accuracy rate of 81.25% and outperformed the accuracy of voting method without using histogram equalization. Penerbit UTHM 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/3661/1/AJ%202018%20%28712%29%20An%20enhancement%20of%20multi%20classifiers%20voting%20method%20for%20mammogram%20image%20based%20on%20image%20histogram%20equalization.pdf Ibrahim, Ashraf Osman and Ahmed, Ali and Azizah, Anik Hanifatul and Lashar, Saima Anwar and Alobeed, Mohamed Alhaj and Kasim, Shahreen and Ismail, Mohd Arfian (2018) An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization. International Journal of Integrated Engineering, 10 (6). pp. 209-213. ISSN 2229-838X
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TR624-835 Applied photography. Including artistic, commercial, medical photography, photocopying processes
spellingShingle TR624-835 Applied photography. Including artistic, commercial, medical photography, photocopying processes
Ibrahim, Ashraf Osman
Ahmed, Ali
Azizah, Anik Hanifatul
Lashar, Saima Anwar
Alobeed, Mohamed Alhaj
Kasim, Shahreen
Ismail, Mohd Arfian
An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
description Breast cancer is one the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the computation methods have greater accurate diagnosis ability. An enhancement of multi classifiers voting technique based on histogram equalization as a preprocessing stage proposed in this paper. The methodology is based on five phases starting by mammogram images collection, preprocessing (histogram equalization and image cropping based region of interest (ROI)), features extracting, classification and last evaluating the classification results. An experimental conducted on different training-testing partitions of the dataset. The numerical results demonstrate that the proposed scheme achieves an accuracy rate of 81.25% and outperformed the accuracy of voting method without using histogram equalization.
format Article
author Ibrahim, Ashraf Osman
Ahmed, Ali
Azizah, Anik Hanifatul
Lashar, Saima Anwar
Alobeed, Mohamed Alhaj
Kasim, Shahreen
Ismail, Mohd Arfian
author_facet Ibrahim, Ashraf Osman
Ahmed, Ali
Azizah, Anik Hanifatul
Lashar, Saima Anwar
Alobeed, Mohamed Alhaj
Kasim, Shahreen
Ismail, Mohd Arfian
author_sort Ibrahim, Ashraf Osman
title An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
title_short An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
title_full An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
title_fullStr An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
title_full_unstemmed An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
title_sort enhancement of multi classifiers voting method for mammogram image based on image histogram equalization
publisher Penerbit UTHM
publishDate 2018
url http://eprints.uthm.edu.my/3661/1/AJ%202018%20%28712%29%20An%20enhancement%20of%20multi%20classifiers%20voting%20method%20for%20mammogram%20image%20based%20on%20image%20histogram%20equalization.pdf
http://eprints.uthm.edu.my/3661/
_version_ 1738581152550092800
score 13.211869

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