Some companies require that only authorized personnel can enter certain restricted areas. Biometric systems normally use RFID (Radio Frequency Identification) cards. However, these systems are not immune to impersonation because cards can be stolen. Other alternatives for the development of security systems consist in the use of facial recognition techniques, which are safer since it is more difficult to impersonate someone, but photographs of the subject can still be used to try to vulnerate the system's security. Therefore, this work proposes the development of a facial recognition application that allows access only to those authorized persons who, during recognition, make a gesture to determine that it is indeed a real subject. The proposed technique comprises three serial stages: face recognition, mouth movement or blink detection, and liveness detection. Several algorithms were analyzed for each stage, choosing the models with which the best performance were obtained. In the first two stages, the Geitgey and Xie methods, respectively, were used for mouth detection, and the Geitgey and Soukupova-Cech algorithms for blinking. Since security systems demand the highest possible accuracy, a new technique for liveness detection from background analysis is proposed, which outperformed the results obtained with Rosebrock's technique, achieving 100% accuracy in a processing time of 6.76 seconds. To evaluate the methods, a database was constructed consisting of 46 videos of fake people and 40 videos of real people performing the opening and closing gesture of the mouth and blinking.
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