# Towards Facial Biometrics for ID Document Validation in Mobile Devices
## 1 Introduction  
Document security has been an important issue since the appearance of the first documents and banknotes. Physical documents are still the first and ultimate authentication method and that is why their protection against spoofing attacks is important. Since the face image is one of the most important biometric components of ID and travel documents, its security is a prominent concern for official issuing organizations [1]. Face recognition techniques have been drawing a lot of attention in the last decade and, particularly, with the development of deep learning tools such as convolutional neural networks, they achieve outstanding accuracy levels. Facial recognition technology impacts the overall security, allowing to automate ID document validation. The pipeline of this process usually follows the differential scenario, which implies that, during the verification procedure, the trusted reference is available. As a source of this reference, various systems may use the face image, a template that is previously stored and secured, or the trusted live captured image of a person from the border control camera. The scenario of 1-1 authentication (verification) is a form of identity validation of a tested individual. At this scale, it is not required to store the remote biometric template/samples database, which eliminates the risks related to identity database theft or fraud at the point of control. The limitation of such a scenario provides face recognition systems with a number of benefits. They can be convenient and safe in applications, such as accessing the security area of personal devices or proving the identity during automated border control when trusted live capture is compared with the face image printed in the passport. The particular case of 1-1 authentication is the so-called match-on-document scenario, which assumes that the trusted and secured biometric template is stored on the documentsthemselves. This strategy allows performing document validation in an offline mode to reduce the information security risks when storing or accessing databases of face images and templates are not allowed. The approach we discuss in this paper is directed to the applications for this scenario. Various face recognition systems usually follow a 1-N authentication scenario which has some peculiarities but which is indeed less relevant to this work. Face recognition systems are threatened by presentation attacks (spoofing attacks) of different kinds. In general, they usually intend to disguise the real subject identity or deceive the system to be impersonated as a different identity [2]. Such impostor attacks can lead to the gaining of illegitimate access by the fraudulent user and pose significant threads for security fields in companies and government sectors [3]. In applications of facial biometric recognition technologies in security systems for ID documents, several aspects are relevant. These solutions tend to become embedded in portable devices, such as smartphones. The specific tendency of certain solutions is to accomplish the offline validation of documents, to avoid risk related to compromising the network connectivity at any level. In this case, the minutia information is extracted from sources of biometric data (faces, fingerprints, iris, etc. ), without storing or accessing databases of face images/templates. The face recognition task for document security is usually constrained by considering frontal face images (in accordance with the ISO/IEC 19794-5 [4]). Since our method is focused on protecting ID and travel documents, we follow that statement. However, it is worth noting that, conceptually, instead of the frontal face image, any other source of biometric data (e.g., fingerprint pattern or iris) may be used in the design of such a validation system. The designed biometric validation system secures the ID document by extracting the template from an enrolled frontal face image and encoding it into an MRC, which is further printed on the document in the specified area (Figure 1).