A New Color Representation for Intensity Independent Pixel Classification in Confocal Microscopy Images

We address the problem of pixel classification in fluorescence microscopy images by only using wavelength information. To achieve this, we use Support Vector Machines as supervised classifiers and pixels components as feature vectors. We propose a representation derived from the HSV color space that...

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Bibliographic Details
Published inAdvanced Concepts for Intelligent Vision Systems Vol. 4678; pp. 597 - 606
Main Authors Lenseigne, Boris, Dorval, Thierry, Ogier, Arnaud, Genovesio, Auguste
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2007
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Color Representation
Color Space
Green Fluorescent Protein
Support Vector Machine
Synthetic Image
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Summary:We address the problem of pixel classification in fluorescence microscopy images by only using wavelength information. To achieve this, we use Support Vector Machines as supervised classifiers and pixels components as feature vectors. We propose a representation derived from the HSV color space that allows separation between color and intensity information. An extension of this transformation is also presented that allows to performs an a priori object/background segmentation. We show that these transformations not only allows intensity independent classification but also makes the classification problem more simple. As an illustration, we perform intensity independent pixel classification first on a synthetic then on real biological images.
ISBN:9783540746065
3540746064
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-74607-2_54