Table of Contents
ISRN Signal Processing
Volume 2011, Article ID 650546, 10 pages
Research Article

Autoadaptive Algorithm for the Stacking-Level Estimation of Membranes in TEM Images

MIPS, Université de Haute-Alsace, 68093 Mulhouse, France

Received 16 November 2010; Accepted 16 December 2010

Academic Editors: S. Lee and Y.-S. Chen

Copyright © 2011 G. Hermann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper introduces an original algorithm for the labeling of the regions of a partitioned image according to the stacking level of membranes in transmission electron microscopy (TEM) images. Image analysis of membrane protein TEM images represents a particular challenging task because of the important noise and heterogeneity present in these images. The proposed algorithm adapts automatically to fluctuations and gray level ranges characterizing each membrane stacking level. Some information about the organization of the objects in the images is introduced as prior knowledge. Three types of qualitative and quantitative experiments have been specifically devised and implemented to assess the algorithm.