# Design and Implementation of a Multi-Modal Biometric System for Company Access Control +
## Materials and Methods  
As stated in the previous section, the goal of this project is the design of an adaptive biometric system for indoor access control and presence monitoring. This system should operate within the scope of a medium/large-sized company which needs to keep some areas restricted to particular employees, depending on their roles or responsibilities. Therefore, proper sensors are supposed to be placed at any check point and in every room or structure in which only authorized users are allowed. The system is intended to handle several different situations:  
* different types of restricted areas have to be accessed by different types of user, depending on their role;
* company employees should be given an easy way to access, since they have to get in and out at least twice a day (they are enrolled in a special database);
* partners, suppliers, or auditors, provided with their own company device (thus known by the company) are submitted to an indirect authentication (e.g., having their template stored on their device and sending it to the company for the matching);
* since the company is open to the public, clients are supposed to access only the reception area;
* some employee is allowed to bring someone else in with them (the system is supposed to know who and where);
* the system works autonomously, but proper human intervention is always possible. The system is intended to operate both in verification and in identification mode. Furthermore, the system is required to guarantee the requirements of the Service Level Agreement (SLA) that affect the expected FAR and FRR values, depending on the different areas or rooms within the company. In a multi-modal biometric system it is worth coupling non-invasive easy-to-use biometrics at lower accuracy together with more robust but expensive parameters, which can intervene whenever a higher degree of confidence is required. Face and iris recognitions have been chosen for the proposed system. The face identifier has been chosen because face recognition is a non-intrusive method of authentication and also requires minimum cooperation from the subject. Moreover, face matching is typically fast, even if it may be not very accurate. One popular approach to face recognition is based on the location, dimensions, and proportions of facial attributes such as eyes, eyebrows, nose, lips, and chin and their spatial relationships. The dimensions, proportions, and physical attributes of a person's face tend to univocally distinguish a single person with good enough confidence. Another approach that is widely used is based on the overall analysis of the face image that represents the face as a weighted combination of a number of canonical faces [14]. Face recognition involves two major tasks: face location and face recognition. Face location is the determination of the location of the face in the input image. Recognizing the located face means that the face is recognized from a general viewpoint (i.e., from any pose). It is worth mentioning that face recognition can be in a static controlled environment where the used is asked for some degree of cooperation, or in a dynamic uncontrolled environment where the user can be completely unaware of being under analysis [15]. The visual texture of the iris is formed during fetal development, and stabilizes during the first two years of life. The complex iris texture carries very distinctive information that is useful for personal recognition of high accuracy. Besides, it is extremely difficult to surgically tamper with the texture of the iris and it is rather easy to detect artificial irises (e.g., designer contact lenses) [5; 16]. Iris recognition is more accurate, but also more invasive because the user has to be very cooperative and the overall acquisition time (pose time plus true acquisition time) can be quite high.