Using fingerprint to identify an individual has been accepted since the nineteenth century, and the fingerprint has become one of the most widely used biometric characteristics. Current modern fingerprint recognition systems are based on the print pattern of the finger surface, and the most commonly used fingerprint sensors are based on frustrated total internal reflection, which produce fingerprint images by reflecting light from only those parts of the skin-glass interface that are not in contact. Those are not robust against spoof attaching, and will fail when finger get dirty, wet or even get flattened associated with age. Nevertheless, in the depth of 220～550 μm under the external fingerprint, there is a layer of skin inside a finger with the same topographical features as the surface (external) fingerprint. This internal layer serves as a “master template” from which the external fingerprint grows. Moreover, within the internal structures of a finger, the sweat pores and microvascular structure will also follow the template. we name it as internal fingerprint, which will not change during the whole life period. Internal fingerprint is difficult to make a fake pattern. In addition, it does not have creases, never dirty, scarred or too wet/dry to make sensor difficult to produce good quality images. Therefore, with High security and robustness, internal fingerprint is ideal as a new way for biometric identification. Currently, there are not many different types of sensors on the market that are able to gather information from the inside of a finger. Optical coherence tomography (OCT) possesses optical sectioning capability and is able to image deep in tissue. By fast standard OCT techniques, such as swept-source OCT (SS-OCT), which can first build a 3-D data volume by point-by-point raster-scanning of A-scan (signal signature along optical axis) , and then a single en face 2-D image at a specific depth can be reconstructed. It needs large memory to store the 3-D data and takes longer time to reconstruct the en face images, but its feasibility is limited. In contrast, full-field OCT (FFOCT) can acquire a single en face image without having to acquire 3-D data set, and therefore, produce much smaller image size (a few Mb) and potentially can be faster. Boccara group has implemented an internal fingerprint reader with InGaAs camera based FFOCT system.In this paper, with cheap CCD camera, we implemented a fast interferometric microscopy with broad band light source for taking the internal fingerprint under the finger skin. The broad band white light laser provided axial resolution of 3.5 μm, with low numerical number illumination, and penetration depth is increased. Thanks to the space incoherence, the arrayed detector can extract the full field en face tomography image without scanning. We demonstrated the 3D structure of the internal fingerprint, including its sweat pores structure, obtained the 2D internal fingerprint image at the speed of 0.4 s per frame. Our work confirmed the capacity of the internal fingerprint for high fidelity biometric identification and provided interferometric microscopy as its reader.