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Proceedings Paper

Detection of low contrasted membranes in electron microscope images: statistical contour validation
Author(s): A. Karathanou; J.-L. Buessler; H. Kihl; J.-P. Urban
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Paper Abstract

Images of biological objects in transmission electron microscopy (TEM) are particularly noisy and low contrasted, making their processing a challenging task to accomplish. During these last years, several software tools were conceived for the automatic or semi-automatic acquisition of TEM images. However, tools for the automatic analysis of these images are still rare. Our study concerns in particular the automatic identification of artificial membranes at medium magnification for the control of an electron microscope. We recently proposed a segmentation strategy in order to detect the regions of interest. In this paper, we introduce a complementary technique to improve contour recognition by a statistical validation algorithm. Our technique explores the profile transition between two objects. A transition is validated if there exists a gradient orthogonal to the contour that is statistically significant.

Paper Details

Date Published: 2 February 2009
PDF: 11 pages
Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510D (2 February 2009); doi: 10.1117/12.805605
Show Author Affiliations
A. Karathanou, Univ. de Haute Alsace (France)
J.-L. Buessler, Univ. de Haute Alsace (France)
H. Kihl, Univ. de Haute Alsace (France)
J.-P. Urban, Univ. de Haute Alsace (France)


Published in SPIE Proceedings Vol. 7251:
Image Processing: Machine Vision Applications II
Kurt S. Niel; David Fofi, Editor(s)

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