# Design and Implementation of a Multi-Modal Biometric System for Company Access Control +
## Materials and Methods
In the _matcher modules_, the extracted features are compared against the stored templates,providing a matching score. These last modules encapsulate the _decision making modules_, which can operate either in verification or identification mode. Moreover, there is the _system database module_, which stores the biometric templates of the enrolled users. The system is intended to be adaptive; this means that it does not have a fixed and predefined behaviour, but its working flow depends on the response of the actual recognition process. Such a response depends on the values of evidence from the single decision modules, the number of previous attempts that did not result in a clear decision, and the evaluation of the quality of the acquisition set-up (lighting, focus, occlusions, and so on). From a numeric value (generally normalized between 0 and 1) that represents the confidence of the matching, each decision module is given three possible different outputs {_YES_, _NO_, _MAYBE_ (? )}, depending on the comparison of that value with some predefined thresholds that divide the interval [0,1] in different sub-intervals (see Figure 1). A decision module outputs the _YES_ value if the obtained score is within the interval [0, \(t_{1}\)] and the user is recognized as one of the enrolled users (in identification mode) or their claimed identity has been confirmed (in verification mode). The output value _NO_ is produced if the obtained score is within the interval [\(t_{2}\), 1] and the user is rejected as if they were impostors. The output value _MAYBE_ (?) results any time the obtained score is within the interval (\(t_{1}\), \(t_{2}\)) and the decision module is not able to make a final decision with a sufficient degree of confidence. The _MAYBE_ (?) value calls for further processing. From a general point of view, there are two main general choices, which involve either the repetition of the identification with a new acquisition of the same biometric, or passing to the analysis of a different biometric. Within the serial paradigm underlining the proposed system, an unsolvable uncontrolled face identification can reasonably be followed by a controlled face identification any time the degree of uncertainty is not very high. This means that if a user obtains an output score that is similar to a genuine user's score (but not similar enough), she/he is asked to try the face identification again, augmenting her/his cooperation during data acquisition, because face processing is always faster and less invasive than iris verification. Conversely, if the obtained score is nearer to the _NO_ interval, the user is asked to submit to iris verification in order to keep a high degree of accuracy in the overall recognition performance. If the unsolvable matching comes from a controlled face identification, it is worth repeating the same process instead of immediately proceeding to iris verification. The number of repetitions can depend on the quality of the resulting matching. Figure 2 represents the general template of the system flow: the choices are ruled by a special threshold: \(t_{3}\), usually set in the middle of the _MAYBE_ interval, as shown in Figure 1. Therefore, there are several different ways of working. For example, a user can be immediately identified and authenticated using their face as they approach the entrance; or they can be asked to repeat the face acquisition in a more controlled way; they can be asked to get closer and the authentication mode can be switched to the verification mode using the iris; again, this last phase can be repeated. Formally, the system works according to some deductive rules which the decision making modules are based on and which represent response behaviors, according to the set-up and status of the acquisition point, the consequent quality of the acquired data, and the actual level of cooperation of the subjects.