A method for cell image segmentation using both local and global threshold techniques

Yuexiang Li, Siu Yeung Cho

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The paper proposed a segmentation method combining both local and global threshold techniques to efficiently segment the cell images. Firstly, the image would be divided into several parts, and the Otsu operation would be used to each of them to detect details. Secondly, main body of the objects would be filtered out by a global threshold algorithm. Finally, based on the previous steps, more advanced segmentation outcomes can be achieved. The experimental results show that this algorithm made better performance at detail recognition, such as the cell antennas, which should be very helpful and important in the medical area.

Original languageEnglish
Title of host publicationMIPPR 2013
Subtitle of host publicationParallel Processing of Images and Optimization and Medical Imaging Processing
DOIs
Publication statusPublished - 2013
Event8th Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2013 - Wuhan, China
Duration: 26 Oct 201327 Oct 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8920
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference8th Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2013
Country/TerritoryChina
CityWuhan
Period26/10/1327/10/13

Keywords

  • Antennas
  • Cell Image
  • Hybrid Methodology
  • Image Segmentation
  • Threshold Techniques

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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