Biometric identification systems have important applications to privacy and security. The most widely used of these, print identification, is based on imaging patterns present in the fingers, hands and feet that are formed by the ridges, valleys and pores of the skin. Most modern print sensors acquire images of the finger when pressed against a sensor surface. Unfortunately, this pressure may result in deformations, characterized by changes in the sizes and relative distances of the print patterns, and such changes have been shown to negatively affect the performance of fingerprint identification algorithms. Optical coherence tomography (OCT) is a novel imaging technique that is capable of imaging the subsurface of biological tissue. Hence, OCT may be used to obtain images of subdermal skin structures from which one can extract an internal fingerprint. The internal fingerprint is very similar in structure to the commonly used external fingerprint and is of increasing interest in investigations of identify fraud. We proposed and tested metrics based on measurements calculated from external and internal fingerprints to evaluate the amount of deformation of the skin. Such metrics were used to test hypotheses about the differences of deformation between the internal and external images, variations with the type of finger and location inside the fingerprint.