Fingerprint recognition is a crucial security technique with a steady growing usage for the identification and verification of people. However, current fingerprint acquisition systems have bound disadvantages, that embody the necessities of physical contact with the acquisition device, and also the presence of undesirable artifacts, like scars, on the surface of the fingerprint. There are various sectors or domains where Biometric authentication plays a vital role, these areas include Internet of Things (IoT), Smartphones, Healthcare, and many more. This paper evaluates the accuracy of a whole framework for the capturing of uninjured, undistorted fingerprints from underneath the skin's surface using Optical Coherence Tomography (OCT), the extraction and conversion of the submerged knowledge into a usable fingerprint and also the matching of such fingerprints. The main objective of this paper is to provide the study of the biometric algorithms, OCT based methods, and their relative comparisons.