This work concerns the problem of post-processing segmented volumetricimages. Such images can arise in fields as diverse as medical imaging,material science, geology and other fields. An application in which toexperiment with different post-processing methods has been written,named Dr. Jekyll. The input images to this application is assumed tobe segmented before it is invoked.
A survey is given of the design goals of the application, as well asan overview of why the C++ language and a selection of libraries werechosen for the implementation.
Special focus is given to the design and implementation of algorithmsin Dr. Jekyll. Effort was made to make the implementation as generic aspossible, without sacrificing runtime speed. It is demonstrated how itis possible to use the template mechanism of C++ to achieve this goal.
Classical imaging algorithms, such a connected components analysis andmathematical morphology, is traditionally applied to binary or graylevel images. This work formulates a version of these algorithms forsegmented images.
Both the application and the algorithms implemented are generic in thesense that they are not tied to a particular field or imagingmodality.
Furthermore the application is designed to be extendable, and toprovide generic mechanism to implement other image processing tools.To further encourage such extendability the application is licensedunder an open source license.