Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis

Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis

In this study, human fecal parasite detection technique based on Filtration and Steady Determinations Thresholds System (F-SDTS) was proposed. The recognition method includes three stages. First stage, a preprocessing subsystem is realized for obtaining unique features after performing noise red...

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Main Authors: Al-Sameraai, Raafat Salih Hadi, Kamarul Hawari, Ghazali, Zeehaida, Mohamed
Format: Article
Language:English
Published: Canadian Centerof Science and Education 2013
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/3713/
http://umpir.ump.edu.my/id/eprint/3713/
http://umpir.ump.edu.my/id/eprint/3713/1/Automated_system_for_diagnosis_intestinal_parasites_by_computerized_image_analysis-fkee_rafaat.pdf
id ump-3713
recordtype eprints
spelling ump-37132017-09-13T03:07:25Z http://umpir.ump.edu.my/id/eprint/3713/ Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis Al-Sameraai, Raafat Salih Hadi Kamarul Hawari, Ghazali Zeehaida, Mohamed TK Electrical engineering. Electronics Nuclear engineering In this study, human fecal parasite detection technique based on Filtration and Steady Determinations Thresholds System (F-SDTS) was proposed. The recognition method includes three stages. First stage, a preprocessing subsystem is realized for obtaining unique features after performing noise reduction, contrast enhancement, segmentation and other morphological process are applied for feature extraction stage of F-SDTSapproach. Second stage, a feature extraction mechanism which is based on five featuresof the three characteristics (shape, shell smoothness, and size) is used. Third stage, Filtration with Steady Determinations Thresholds System (F-SDTS) classifier is used for recognition process using the ranges of feature values as a database to identify and classify the type of parasite. The technique enables to classify two different parasite eggs from their microscopic images which are roundworms (Ascaris lumbricoides ova, ALO) and whipworms (Trichuris trichiura ova, TTO). Finally, simulation result shows overall success rates are almost 93% and 94% in Ascaris lumbricoides and Trichuris trichiura, respectively. Canadian Centerof Science and Education 2013 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3713/1/Automated_system_for_diagnosis_intestinal_parasites_by_computerized_image_analysis-fkee_rafaat.pdf Al-Sameraai, Raafat Salih Hadi and Kamarul Hawari, Ghazali and Zeehaida, Mohamed (2013) Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis. Modern Applied Science, 7 (5). pp. 98-114. ISSN 1913-1844 (printed), 1913-1852 (online) http://dx.doi.org/10.5539/mas.v7n5p98
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Al-Sameraai, Raafat Salih Hadi
Kamarul Hawari, Ghazali
Zeehaida, Mohamed
Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
description In this study, human fecal parasite detection technique based on Filtration and Steady Determinations Thresholds System (F-SDTS) was proposed. The recognition method includes three stages. First stage, a preprocessing subsystem is realized for obtaining unique features after performing noise reduction, contrast enhancement, segmentation and other morphological process are applied for feature extraction stage of F-SDTSapproach. Second stage, a feature extraction mechanism which is based on five featuresof the three characteristics (shape, shell smoothness, and size) is used. Third stage, Filtration with Steady Determinations Thresholds System (F-SDTS) classifier is used for recognition process using the ranges of feature values as a database to identify and classify the type of parasite. The technique enables to classify two different parasite eggs from their microscopic images which are roundworms (Ascaris lumbricoides ova, ALO) and whipworms (Trichuris trichiura ova, TTO). Finally, simulation result shows overall success rates are almost 93% and 94% in Ascaris lumbricoides and Trichuris trichiura, respectively.
format Article
author Al-Sameraai, Raafat Salih Hadi
Kamarul Hawari, Ghazali
Zeehaida, Mohamed
author_facet Al-Sameraai, Raafat Salih Hadi
Kamarul Hawari, Ghazali
Zeehaida, Mohamed
author_sort Al-Sameraai, Raafat Salih Hadi
title Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
title_short Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
title_full Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
title_fullStr Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
title_full_unstemmed Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
title_sort automated system for diagnosis intestinal parasites by computerized image analysis
publisher Canadian Centerof Science and Education
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/3713/
http://umpir.ump.edu.my/id/eprint/3713/
http://umpir.ump.edu.my/id/eprint/3713/1/Automated_system_for_diagnosis_intestinal_parasites_by_computerized_image_analysis-fkee_rafaat.pdf
first_indexed 2023-09-18T21:58:10Z
last_indexed 2023-09-18T21:58:10Z
_version_ 1777414218981572608

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