Tuan Muda, Tuan Zalizam and Abdul Salam, Rosalina (2013) Comparative analysis on blood cell image segmentation. In: 2nd International Symposium on Computer, Communication, Control and Automation (3CA 2013), 1-2 December 2013, Singapore.

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Abstract

Image segmentation is an important phase in image recognition system.In medical imaging such as blood cell analysis, it becomes a crucial step in quantitative cytophotometry. Currently, blood cell images become predominantly valuable in medical diagnostics tools.In this paper, we present a comparative analysis on several segmentation algorithms. Three selected common approaches, that are Fuzzy c-means, K-means and Mean-shift were presented.Blood cell images that are infected with malaria parasites at various stages were tested.The most suitable method that is K-means was selected. K-means has been enhanced by integrating Median-cut algorithm to further improve the segmentation process.The proposed integrated method has shown a significant improvement in the number of selected regions.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Segmentation, Blood cell images, means-shift, fuzzy e-means, Median-cut
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	College of Arts and Sciences
Depositing User:	Mr. Tuan Zalizam Tuan Muda
Date Deposited:	12 Mar 2014 08:26
Last Modified:	12 Mar 2014 08:26
URI:	https://repo.uum.edu.my/id/eprint/10017

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