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Malaria parasites segmentation in red blood cells images using mean-shift and median-cut


Tn. Muda, Tn. Zalizam and A Salam, Rosalina (2010) Malaria parasites segmentation in red blood cells images using mean-shift and median-cut. In: 2010 International Conference on Intelligent Network and Computing (ICINC 2010), 26-28 November 2010, Kuala Lumpur, Malaysia. IEEE Computer Society, pp. 1-7. ISBN 978-1-4244-8270-2

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Abstract

This paper describes a better approach on merging segmentation algorithms of Mean-shift and Median-cut for color blood cells images. The proposed method applies in two major components of both algorithms. Before starting the analysis, image pre-processing procedure was applied to improve the image before altering the RGB colour space to LUV colour space. After that Mean-shift segmentation will initiate the next process. Since the Means-shift algorithm carry out low level segmentation, some of the region has no semantic meaning. To combat this predicament, median-cut algorithm was introduced to unite the gap left by the meansshift. The results showed better improvement in terms of the contour extraction for further processing.

Item Type: Book Section
Additional Information: Co-sponsored by the International Association of Computer Science and Information Technology (IACSIT) and IEEE, and supported by Universiti Putra Malaysia (UPM) and Universiti Teknologi MARA (UiTM).
Uncontrolled Keywords: Color image segmentation, k-means segmentation, mean-shift, median-cut, edge detection
Subjects: Q Science > QA Mathematics
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 13 Mar 2011 07:53
Last Modified: 13 Mar 2011 07:53
URI: http://repo.uum.edu.my/id/eprint/2771

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