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Nucleus Recognition of Uterine Cervical Pap-Smears using Fuzzy Reasoning Rule

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2008, 13(3), pp.179-188
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Kwang Baek Kim ORD ID 1 SONG,DOO HEON 2

1신라대학교
2용인송담대학

Accredited

ABSTRACT

In this paper, we apply a set of algorithms to classify normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining 1400 microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.

Citation status

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