2.2.1. TGS-CVBR®

The real-time video of the camera capture (640 × 480 resolution) was displayed on a monitor together with the three fixed guidelines, as is shown in Figure 2 (step 2, right side). This algorithm provided feedback to the user on how he/she was positioning the wrist and was used for database collection (UC3M-CV1, in this case) and user recognition (combined with PIS-CVBR®). The guidelines were useful because they fixed the user's wrist, obtaining scale-orientation-invariant images in order to improve the recognition algorithm task: the largest horizontal guideline sets the wrist orientation, and the two smaller guidelines establish the distance between the wrist and the camera.

**Figure 2.** Three-Guideline Software for Contactless Vascular Biometric Recognition (TGS-CVBR®), wrist positioning steps (based on [1]). (**a**) Step 1: the location of the wrist groove line. (**b**) Step 2: match of the wrist groove print and the guideline.

This software was developed using Python™ 3.4.2 due to the quick and easy way to access to the USB camera and the well-integration of the language with deep learning libraries, in order to be used in future works.

The user should follow the steps shown in Figure 2:

