Stereoscopic depth-detection for handling and manipulation tasks in a scanning electron microscope

In micro- and nanotechnology, handling and manipulation processes are important. Because of the size of the structures, scanning electron microscopes (SEM) are employed. For precise handling, there is a need to know the position of the objects and the tools in all three dimensions of space. For solving this problem, the 2D information of SEM images is not sufficient. There is a need for 3D information. By generating a pair of stereoscopic images, the third dimension (relative depth) can be determined. In this work, a stereo algorithm based on a biologically motivated energy model utilizing a new coherence detection analysis algorithm is proposed. This stereo approach provides a high density and sharp disparity map in sub-pixel accuracy and is invariant to different contrasts in the input images. In addition, a new filter is presented which detects low-texture regions and removes the noise in the disparity map on these positions. In the application section of this work the properties of the stereo algorithm are verified