Human parasitic worm detection using image processing technique

Intestinal parasites of protozoa and helminthes may cause disease or even death to animals and humans. In a current study of fecal sample examination to detect parasites, a technologist examines images manually using a lighted microscope. This method of examination is known to be inefficient when it...

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Main Authors:	R. S., Hadi, Z., Khalidin, Kamarul Hawari, Ghazali, M., Zeehaida
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2012
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/26968/ http://umpir.ump.edu.my/id/eprint/26968/ http://umpir.ump.edu.my/id/eprint/26968/1/Human%20parasitic%20worm%20detection%20using%20image%20processing%20technique.pdf

id	ump-26968
recordtype	eprints
spelling	ump-269682020-03-20T03:00:49Z http://umpir.ump.edu.my/id/eprint/26968/ Human parasitic worm detection using image processing technique R. S., Hadi Z., Khalidin Kamarul Hawari, Ghazali M., Zeehaida TK Electrical engineering. Electronics Nuclear engineering Intestinal parasites of protozoa and helminthes may cause disease or even death to animals and humans. In a current study of fecal sample examination to detect parasites, a technologist examines images manually using a lighted microscope. This method of examination is known to be inefficient when it involves a large number of samples. On top of that, it is very important to introduce a system that is capable of assisting the technologist in the examination of fecal samples. In this paper, an automatic process is proposed to detect different types of parasites from fecal samples using an image processing technique. Image processing techniques have been introduced to automatically screen the existence of parasites in human fecal specimens. This process involves methods such as noise reduction, contrast enhancement, segmentation, and morphological analysis. At the classification stage, we propose a simple classification method using logical threshold, whereby the ranges of feature values have been identified to classify the type of parasite. The proposed system has been tested with 100 parasite images of each class, which promotes accuracy. IEEE 2012 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26968/1/Human%20parasitic%20worm%20detection%20using%20image%20processing%20technique.pdf R. S., Hadi and Z., Khalidin and Kamarul Hawari, Ghazali and M., Zeehaida (2012) Human parasitic worm detection using image processing technique. In: IEEE Symposium on Computer Applications and Industrial Electronics (ISCAIE 2012), 3-4 December 2012 , Kota Kinabalu, Sabah. pp. 196-201.. ISBN 978-1-4673-3033-6 https://doi.org/10.1109/ISCAIE.2012.6482095
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 R. S., Hadi Z., Khalidin Kamarul Hawari, Ghazali M., Zeehaida Human parasitic worm detection using image processing technique
description	Intestinal parasites of protozoa and helminthes may cause disease or even death to animals and humans. In a current study of fecal sample examination to detect parasites, a technologist examines images manually using a lighted microscope. This method of examination is known to be inefficient when it involves a large number of samples. On top of that, it is very important to introduce a system that is capable of assisting the technologist in the examination of fecal samples. In this paper, an automatic process is proposed to detect different types of parasites from fecal samples using an image processing technique. Image processing techniques have been introduced to automatically screen the existence of parasites in human fecal specimens. This process involves methods such as noise reduction, contrast enhancement, segmentation, and morphological analysis. At the classification stage, we propose a simple classification method using logical threshold, whereby the ranges of feature values have been identified to classify the type of parasite. The proposed system has been tested with 100 parasite images of each class, which promotes accuracy.
format	Conference or Workshop Item
author	R. S., Hadi Z., Khalidin Kamarul Hawari, Ghazali M., Zeehaida
author_facet	R. S., Hadi Z., Khalidin Kamarul Hawari, Ghazali M., Zeehaida
author_sort	R. S., Hadi
title	Human parasitic worm detection using image processing technique
title_short	Human parasitic worm detection using image processing technique
title_full	Human parasitic worm detection using image processing technique
title_fullStr	Human parasitic worm detection using image processing technique
title_full_unstemmed	Human parasitic worm detection using image processing technique
title_sort	human parasitic worm detection using image processing technique
publisher	IEEE
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/26968/ http://umpir.ump.edu.my/id/eprint/26968/ http://umpir.ump.edu.my/id/eprint/26968/1/Human%20parasitic%20worm%20detection%20using%20image%20processing%20technique.pdf
first_indexed	2023-09-18T22:42:19Z
last_indexed	2023-09-18T22:42:19Z
_version_	1777416997175296000

Human parasitic worm detection using image processing technique

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