The advanced module for complex measurement tasks
This function offers threshold operators for images necessary to identify the objects based on gray color values. The objects can also be quickly identified at a mouse click using "e;region growing"e;. These methods are supplemented by complex methods for segmentation, including dynamic and automatically generated threshold as well as edge detection. Dynamic discrimination allows you to differentiate and emphasize important details from the background. Valley detection makes dark lines visible. Even weakly defined edges can be clearly identified using several detection techniques. The result is a binary image in which all specimen pixels are white and all background pixels black.
Binary image processing
Numerous functions ensure that the binary image is optimally prepared for measurement. They include linking, masking, and filling voids. Artifacts can be removed easily and contours smoothened. During "e;skeletonizing"e; objects are thinned to a 1-Pixel-line or separated from each other using a background skeleton.