Abstract: The dermal depth of different individual figures varies, which reduces the application universality of many existing methods that extract the internal and external fingerprints from the optical coherence tomography (OCT) images based on dermal depth. This paper proposes an adaptive OCT internal and external fingerprint extraction method based on structure point clustering. Firstly, an adaptive clustering method was proposed with improved similarity calculation and clustering termination condition, to adaptively separate the structural points of the stratum corneum and the papillary layer. Secondly, a two-step far to near pseudo- structure point removal algorithm was proposed to remove the pseudo-structure points caused by the sweat glands and other internal tissues, and thereafter the precise contours of the stratum corneum and papillary layer were obtained by interpolation fitting. Finally, OCT internal and external fingerprints were obtained after fingerprint stitching and enhancement. The experimental results show that the proposed method can adapt to the dermal depth of different individuals, and achieve simultaneous extraction of recognizable, large-area and high-resolution internal and external fingerprints from OCT three-dimensional data with high universality and robustness.