Data gathered during photo-identification research allow researchers to assess population dynamics, movement and behavior. The use of digital images has allowed researchers to take advantage of commercially available image analysis software as well as develop computer-assisted image analysis techniques to facilitate the storage and analysis of images. For bottlenose dolphin (Tursiops truncatus), individuals can often be discerned using blemishes, nicks, notches, and/or scars on their dorsal fins.
There are currently a number of active bottlenose dolphin photo-identification research programs that rely on the use of dorsal fin markings observed in digital images to distinguish and catalog individuals. Depending on the intensity of survey efforts and size of study area, photo-identification catalogs can grow at a rapid pace. As catalogs grow, the process of matching surveyed individuals to existing catalog entries can become very time-consuming.
While database management systems (DBMS) have been increasingly employed to store and manage textual and numerical data associated with photo-identification research, the management and analysis of images is often performed manually outside of the DBMS. FinBase is a customized Microsoft Access database system that not only stores and manages textual and numerical data from photo-identification surveys, but also performs many of the tasks associated with image management and analysis. A companion ArcGIS™ Extension called the FinBase Mapping Tool was also developed to allow users to easily query FinBase while in a GIS environment and spatially display output. A very brief description of the database system and mapping tool are provided. Both are available for download.
FinBase is provided to the public as part of the FinBase Technology Transfer Project, which is a product of the Marine Mammals program, in the Protected Areas and Resources Branch.