Background Extraction in Electron Microscope Images of Artificial Membranes

On-line analysis of Transmission Electron Microscope (TEM) images is a field with great interest that opens up new prospects regarding automatic acquisitions. Presently, our work is focused on the automatic identification of artificial membranes derived from 2D protein crystallization experiments. Objects recognition at medium magnification aims to control the microscope in order to acquire interesting membranes at high magnification. A multiresolution segmentation technique has been proposed for the image partition. This paper presents an analysis of this partition to extract the background. To achieve this goal in very noisy images, it is essential to suppress false contours as they split the background into multiple regions. Statistical properties of such regions are not always sufficient for their identification as background. The analysis of these regions contours was therefore considered. In the proposed solution, the elimination of false contours is based on the statistical examination of the perpendicular gradient component along the contour. After this improved segmentation, the background extraction can be easily effectuated since this resulting region appears bright and large.