Handwriting recognition systems rely on the existence of a corpus for training recognition models and evaluating accuracy. Creating a handwriting recognition corpus for the Bushman languages of southern Africa is difficult due to the complexities of the script used to represent them and the fact that this script cannot be represented using Unicode. To solve this problem, a semi-automatic Web-based tool was developed to segment, capture and encode the Bushman text. A case study demonstrated how the tool could be used to create a Bushman handwriting corpus with few errors.