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Blood cell image segmentation based on the Hough transform and fuzzy curve tracing

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Segmentation of blood cells is a difficult task because of the presence of noise and the substantial brightness changes within cells in microscopy images. A method based on the Hough transform and fuzzy curve tracing is proposed in this paper. The Hough transform is used to detect the rough circular boundary of each cell. Then, fuzzy curve tracing is employed to detect the exact cell boundary. This approach reduces the effects of noise and the uneven brightness within the cells effectively. In addition, it can even separate slightly overlapping cells. Experiment results show that the proposed method is superior to many existing segmentation methods. © 2011 IEEE.
Original languageEnglish
Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
Pages1696-1701
Volume4
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China
Duration: 10 Jul 201113 Jul 2011

Publication series

Name
Volume4
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
PlaceChina
CityGuilin, Guangxi
Period10/07/1113/07/11

Research Keywords

  • Blood Cell
  • Fuzzy curve tracing
  • Hough transform
  • Image segmentation

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