Automatic detection of specular reflections in uterine cervix images

Gali Zimmerman-Moreno, Hayit Greenspan

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

55 Scopus citations


Specular reflections strongly affect the appearance of images, and usually hinder the computer vision algorithms applied to them. This is particularly the case with uterine cervix images. The highlights created by specular reflections are a major obstacle in the way of automatic segmentation of such images. We propose a method for the detection of specularities in cervix images that utilizes intensity, saturation and gradient information. A two-stage segmentation process is proposed for the identification of highlights. First, coarse regions that contain the reflections are defined. Second, probabilistic modeling and segmentation is used to achieve a precise segmentation inside the coarse regions. The resulting regions are filled by propagating the surrounding color information. The efficiency of the method for cervix images is demonstrated.

Original languageEnglish
Title of host publicationMedical Imaging 2006
Subtitle of host publicationImage Processing
StatePublished - 2006
Externally publishedYes
EventMedical Imaging 2006: Image Processing - San Diego, CA, United States
Duration: 13 Feb 200616 Feb 2006

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6144 III
ISSN (Print)1605-7422


ConferenceMedical Imaging 2006: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA


  • Cervigram
  • GMM
  • Highlights
  • Image quality
  • Segmentation
  • Specular reflections
  • Statistical methods
  • Uterine cervix images


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