Tattoos have been used for many years to assist law enforcement in investigations leading to the identification of criminals and victims. A tattoo is an elective biometric trait that could contain more discriminative information to support person identification than traditional soft biometrics such as age, gender and race. While some research has been done in the area of image-based tattoo detection and retrieval, it is not a mature domain. There are no common datasets to evaluate and develop operationally-relevant tattoo recognition applications.
To address this shortcoming, the NIST Tattoo Recognition Technology Challenge (Tatt-C) database was developed as an initial tattoo research corpus that addresses use cases representative of operational scenarios. The Tatt-C database represents an initial attempt to provide a set of ground-truthed tattoo images focused on, but not limited to, five primary use cases. This paper describes the details of the database along with the experimental protocols and test cases that should be followed, which will enable consistent performance comparison of tattoo recognition methods.