COLOR SEGMENTATION OF MGG COLORED CYTOLOGICAL IMAGES USING NON LINEAR OPPONENT COLOR SPACES

Hélène Gouinaud, Lara Leclerc

Abstract

This paper presents a color image segmentation method for the quantification of viable cells from samples obtained after cytocentrifugation process and May Grunwald Giemsa (MGG) coloration and then observed by optical microscopy. The method is based on color multi-thresholding and mathematical morphology processing using color information on human visual system based models such as CIELAB model, LUX (Logarithmic hUe eXtension) model and CoLIP (Color Logarithmic Image Processing) model, a new human color vision based model also presented in this article. The results show that the CoLIP model, developed following each step of the human visual color perception, is particularly well adapted for this type of images.

Keywords
color; cytology; human vision; image analysis; logarithmic image processing; segmentation

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DOI: 10.5566/ias.v32.p167-174

Image Analysis & Stereology
EISSN 1854-5165 (Electronic version)
ISSN 1580-3139 (Printed version)