Part of understanding aquatic ecosystems requires that zooplanktons be studied; achieving this type of underwater study requires that the traditional two-dimensional (2D) cameras be upgraded to three-dimensional (3D) cameras to successfully capture the zooplanktons. One such study of zooplanktons is of Harmfiil Algal Blooms (HAB's) in coastal waters to prevent them from being consumed due to their toxicity (HAB Buoy project); the study concentrates on the automated recognition of HAB's so that government scientists can have advanced knowledge of their abundance. This thesis describes software whose aims are set by the HAB Buoy project to present confocal images of zooplankton as a 3D Image (Model), this Model is then to be used by the software to create multiple images of the Model from different angles for the recognition of these HAB's. Recognition of objects requires taxonomic information, the software allows for this by separating and labelling parts of the zooplankton by experts. Transparency in the Model could also be used by experts for further taxonomic information and is also to be made a feature in the software. The software described in the thesis was successful to the point of which a Model could be created from a stack of confocal images, sectioned, and then unwanted parts deleted, unfortunately the labelling of these parts, transparency, and images made from different angles were never successfully achieved.School of Computing, Communications and Electronics, HAB Buoy Project