Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering

The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malay...

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Main Authors: A.S., Abdul Nasir, Mohd Yusoff, Mashor, Prof. Dr., Zeehaida, Mohamed, Dr.
Other Authors: aimi_salihah@yahoo.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2013
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/29817
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spelling my.unimap-298172013-11-14T07:52:10Z Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering A.S., Abdul Nasir Mohd Yusoff, Mashor, Prof. Dr. Zeehaida, Mohamed, Dr. aimi_salihah@yahoo.com yusoff@unimap.edu.my zeehaida@kck.usm.my Malaria Image processing Colour segmentation C-Y colour model K-Means clustering The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Postgraduates Student Association Ireland (MyPSI), 18th - 19th June 2012 at Putra World Trade Center (PWTC), Kuala Lumpur, Malaysia. Malaria is a life threatening disease that is responsible for nearly one million deaths each year. With the large number of cases diagnosed over the year, rapid detection and accurate diagnosis which facilitates prompt treatment is an essential requirement to control malaria. Due to the requirement for rapid detection of malaria, the current study has proposed the colour image segmentation of malaria parasites that has been applied on malaria images of P. vivax species. Here, the proposed method provides a basic step for detection of the presence of malaria parasites in thin blood smears. In order to obtain the segmented parasite, the malaria image will first be enhanced using global contrast stretching. Then, an unsupervised segmentation technique namely k-means clustering algorithm is used to segment the parasite from its complicated blood cells background. Here, the five colour components of C-Y colour model which are R-Y, B-Y, luminance, hue and saturation components are analyzed to identify the colour component that perform significant segmentation performance. Finally, median filter and seeded region growing area extraction algorithms have been applied in order to smooth the image and remove any unwanted regions from the image, respectively. The proposed segmentation method has been analyzed using 50 malaria images of gametocyte stage. Overall, the results indicate that k-means clustering using saturation component of C-Y colour model has produced the best segmentation performance with segmentation accuracy of 99.19%. 2013-11-14T07:52:10Z 2013-11-14T07:52:10Z 2012-06-18 Working Paper p. 99 - 107 978-967-5760-11-2 http://hdl.handle.net/123456789/29817 en Proceedings of the The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012); Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Malaria
Image processing
Colour segmentation
C-Y colour model
K-Means clustering
spellingShingle Malaria
Image processing
Colour segmentation
C-Y colour model
K-Means clustering
A.S., Abdul Nasir
Mohd Yusoff, Mashor, Prof. Dr.
Zeehaida, Mohamed, Dr.
Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
description The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Postgraduates Student Association Ireland (MyPSI), 18th - 19th June 2012 at Putra World Trade Center (PWTC), Kuala Lumpur, Malaysia.
author2 aimi_salihah@yahoo.com
author_facet aimi_salihah@yahoo.com
A.S., Abdul Nasir
Mohd Yusoff, Mashor, Prof. Dr.
Zeehaida, Mohamed, Dr.
format Working Paper
author A.S., Abdul Nasir
Mohd Yusoff, Mashor, Prof. Dr.
Zeehaida, Mohamed, Dr.
author_sort A.S., Abdul Nasir
title Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
title_short Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
title_full Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
title_fullStr Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
title_full_unstemmed Colour image segmentation of malaria parasites in thin blood smears using C-Y colour model and K-Means clustering
title_sort colour image segmentation of malaria parasites in thin blood smears using c-y colour model and k-means clustering
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/29817
_version_ 1643795577950961664
score 13.214268