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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/10174

Title: Colour image segmentation of tuberculosis bacilli in Ziehl-Neelsen-stained tissue images using moving K-Mean clustering procedure
Authors: M. K. Osman
Mohd Yusoff, Mashor, Prof Madya Dr.
Z. Saad
H. Jaafar
???metadata.dc.contributor.url???: khusairi@ppinang.uitm.edu.my
Keywords: Colour image segmentation;Tuberculosis bacilli;Tissue section;Moving k-mean clustering
Issue Date: May-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p.215-220
Series/Report no.: Proceedings of the 4th Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation 2010
Abstract: Segmentation of tuberculosis bacilli in Zeihl-Neelsen tissue slide images is a crucial step in computerassisted tuberculosis bacilli detection. In this paper, an automatic colour image segmentation using moving k-mean clustering was proposed. First, initial filter is used to remove the tissues images which remain blue after counterstaining process. After that, moving k-mean clustering using green component of RGB colour model and Rycomponent of C-Y colour model are used to segment the TB bacilli from its undesirable background which also remains red even after decolourization process. Then a 5×5 median filter and region growing was used to eliminate small regions and noises. The proposed methods have been analysed for several TB slide images under various conditions. Experimental results indicate that the proposed techniques were successfully segment TB bacilli from its background.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ezproxy.unimap.edu.my:2080/stamp/stamp.jsp?tp=&arnumber=5489226
http://hdl.handle.net/123456789/10174
ISBN: 978-1-4244-7196-6
Appears in Collections:Conference Papers
Mohd Yusoff Mashor, Prof. Dr.

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