Authors
Kan Jiang, Qing-Min Liao, Sheng-Yang Dai
Publication date
2003/11/5
Conference
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No. 03EX693)
Volume
5
Pages
2820-2825
Publisher
IEEE
Description
In this paper, a novel white blood cell (WBC) segmentation scheme using scale-Space filtering and watershed clustering is proposed. In this scheme, nucleus and cytoplasm, the two components of WBC, are extracted respectively using different methods. First, a sub image containing WBC is separated from cell image. Then, scale-space filtering is used to extract nucleus region from sub image. Later, a watershed clustering in 3-D HSV histogram is processed to extract cytoplasm region. Finally, morphological operations are performed to obtain the entire connective WBC region. By using feature space clustering technique, this scheme successfully avoids the variety and complexity in image space, and can effectively extract various WBC regions from cell images of peripheral blood smear. Experiments demonstrate that the proposed scheme performs really well and HSV space is more appropriate than RGB space …
Total citations
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Scholar articles
K Jiang, QM Liao, SY Dai - Proceedings of the 2003 International Conference on …, 2003