Algoritmos de procesamiento de señales para el reconocimiento facial y de voz empleando redes neuronales

Abstract

The present titling work deals with the development of an access control system through facial and voice recognition, for the authentication of people in a home. Currently, the levels of insecurity have increased and this has led to an increase in theft and damage to real estate due to the low level of security in a home. The device developed in this project is based on a bimodal access biometric, through machine learning and neural networks, a subfield of Artificial Intelligence. The system has two authentication methods: facial and voice, for which neural network models designed by the researcher were used with the stages of: database formation, image and audio processing, and neural network design. He implements two methods of facial and voice authentication to avoid identity theft, a camera is responsible for capturing the person's face and performing recognition through the neural network, if the user is registered, the microphone is activated to capture the key of access and process it through the neural network, to record the data a LAMP server is used where the system information and user notifications are stored through the Telegram application. This project is aimed at controlling the access of people to a home, avoiding the use of traditional authentication methods.