Tattoos have been successfully employed to assist law enforcement in the identification of criminals and victims. Due to various privacy issues in acquiring images containing tattoos, only a limited number of databases exist. This lack of databases has slowed down the development of new tattoo segmentation and retrieval methods. In our work, we propose a new unsupervised generator that allows generating a large number of semi-synthetic images with tattooed subjects. To successfully generate realistic images, a database including the respective skin segmentation map is also proposed. Using this new generator and the skin database, 5,500 semi-synthetic images were created and evaluated for the tattoo segmentation use case. Experimental results on real data show the usefulness of using semi-synthetic images to train semantic segmentation algorithms: several manually mislabelled real samples were successfully corrected. The tattoo generator code, the skin database and generated images have been made available at https://dasec.h-da.de/hda-sstd/.