## 2 Related Work
### OCT Dataset  
The corresponding relationship between the B-scan images acquired by OCT technology and the real sub-dermal structures of fingertips is shown in Figure 3. The outermost layer, which comes into daily contact with the external environment, is called the epidermis. On the outer surface of the epidermis, the tough part with friction ridge structures is known as the stratum corneum. The part beneath the epidermis is the dermis, which provides most of the skin's elasticity and strength. Sweat glands are distributed between the epidermis and the dermis, usually in a spiral or oval shape, and are responsible for secreting sweat to regulate body temperature. The special structure located between the stratum corneum and the dermis is the viable epidermis junction layer. This layer has unique undulating features, called the internal fingerprint, which provides a basis for identifying an individual's identity. The bona fide samples used in the experiment were collected from 160 white-collar and blue-collar workers aged between 20 and 60, with a ratio of approximately 1:4. All the volunteers who participated in the fingerprint collection were Chinese. A total of 2,039,800 slices were collected. Due to the issue of the slicing angle during scanning, the first 400 B-scan slices of each volume of data do not have a relatively complete tissue structure. Therefore, in the experiment, only the last 1000 scanned slices of each volume of data were selected as the source of the bona fide sample dataset. In this paper, 21 kinds of materials are used to make the spoof sample dataset, with a total of 525 groups of spoof sample data. The spoof sample dataset is roughly divided into two categories. The first category uses a single material, which can only ensure that the surface threads of the samples are similar to those of bona fide fingerprints. The materials used include epoxy resin, Elmer's glue, handmade white glue, conductive silica gel, etc. The other category of spoof samples has a double-layer tissue structure similar to that of the OCT images of bona fide samples, which increases the difficulty of the anti-spoofing task. This type of spoof sample is composed of eight kinds of materials, including transparent silica gel, flesh-colored silica gel, etc. As shown in Table 1, for spoof samples made from fingerprints of different materials, the OCT scanning results also vary. Ordinary single-layer silica gel samples have a simple organizational structure. For the double-layer film fingerprint structure, as different materials are added during the production of spoof samples, the refractive index of light during OCT acquisition is different in the two materials. Therefore, an obvious double-layer structure will appear, posing a great challenge to current anti-spoofing methods. Polystyrene microspheres and conductive silver particles in the fingerprint film can  
Figure 3: Correspondence between B-scan and fingertip tissue structure. simulate the sub-dermal sweat gland tissue of bona fide fingerprints, which also makes it difficult to distinguish between bona fide and spoof samples. In response to the need for feature extraction of the organizational structure of OCT fingerprints, this paper establishes an OCT layer segmentation dataset. A total of 1050 B-scan images are randomly selected from bona fide samples to form the layer segmentation dataset, and manual annotations are carried out for the glass layer, stratum corneum layer, and viable epidermis junction layer of the OCT fingerprint samples. In this paper, each B-scan image in the dataset is divided into three regions, which are parts (c), (d), and (e) of Figure 4, respectively. The open-source image annotation software used is Labelme v4.5.12. As an image annotation tool, it is often used in the field of image segmentation. After using marking points of different colors to encircle the contours of each layer of the tissue structure in the B-scan image, Labelme will output the final annotation result.