Multi-factor Biometric Authenticator

This project explores the integration of face and voice recognition systems, utilizing Python for development and implementation.The face recognition component incorporates techniques such as white balance correction, skin-like region segmentation, facial feature extraction, and face image extraction.System testing demonstrates satisfactory performance in recognizing faces within predefined limits, including the detection and identification of multiple faces in real-time acquired images.Concurrently, the voice recognition module employs advanced algorithms to analyze and identify unique vocal characteristics, contributing an additional layer of security and user authentication.The combined face and voice recognition system aims to enhance accuracy and reliability, offering a multimodal approach for comprehensive biometric identification.The proposed automated system is designed for identifying individuals from still images and video frames, allowing real-time tracking of target objects in live video streams.Python serves as the programming language, providing flexibility for researchers and developers to explore biometric systems intricacies.The integration of face and voice recognition technologies opens avenues for applications in security systems, access control, and human-computer interaction, where multimodal biometrics can significantly improve overall system performance and reliability..