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  1. Home
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  4. Blood cell image segmentation using hybrid K-means and median-cut algorithms
 
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Blood cell image segmentation using hybrid K-means and median-cut algorithms

Journal
Proceedings - 2011 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011
Date Issued
2011
Author(s)
Muda T.Z.T.
Salam R.A.
DOI
10.1109/ICCSCE.2011.6190529
Abstract
In blood cell image analysis, segmentation is crucial step in quantitative cytophotometry. Blood cell images have become particularly useful in medical diagnostics tools for cases involving blood. In this paper, we present a better approach on merging segmentation algorithms of K-means and Median-cut for colour blood cells images. Median-cut technique will be employed after comparing best outcomes from Fuzzy c-means, K-means and Means-shift. We used blood cell images infected with malaria parasites as cell images for our research. The result of proposed method shows better improvement in terms of object segmentations for further feature extraction process. � 2011 IEEE.
Subjects

Blood Cell Images

Fuzzy c-means

K-means

Means-shift

Median-cut

Segmentation

Blood cell images

Fuzzy C mean

K-means

Means-shift

Median-cut

Blood

Cells

Control systems

Cytology

Feature extraction

Fuzzy systems

Image segmentation

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