We describe a method that performs automated recognition of individual laetherback turtles within a large nesting population. With only minimal preprocessing required of the user, we prove able to produce unsupervised matching results. The matching is based on the Scale-Invariant Feature Transform by Lowe. A strict condition posed by biologists reads that matches should not be missed (no false negatives). A robust criterion is defined to meet this requirement. Results are reported for a considerable sample of leatherbacks.
P. Perner
Lecture Notes in Artificial Intelligence
Multimedia Understanding through Semantics, Computation and Learning
Signals and Images

Pauwels, E., de Zeeuw, P., & Buonantony, D. M. (2008). Leatherbacks matching by automated image recognition. In P. Perner (Ed.), Advances in Data Mining - Medical Applications, E-Commerce, Marketing and Theoretical Aspects (pp. 417–425). Springer.