Face Recognition- Based Security for Social Media Login

Social Networking has become today’s lifestyle and anyone can easily receive information about everyone in the world. It is very useful if a personal identity can be obtained from the device and also connected to social networking. Therefore, we proposed a face recognition system. Our system is designed in the form of an application developed on desktop. We also applied the Machine learning as an information viewer to the users. The result of testing shows that the system is able to recognize face samples with the average percentage of 85 percentage with the total computation time for the face recognition system reached 7.45 seconds, and the average augmented reality translation time is 1.03 seconds to get someone’s information. Face authentication has emerged as a prominent method for identity verification, leveraging the unique biometric features of individuals to enhance security and user convenience. This paper presents the design and implementation of a face authentication system that utilizes advanced machine learning algorithms and image processing techniques to accurately and efficiently verify user identities. The system captures facial images in real-time and processes them to extract distinguishing features, which are then compared against a secure database of registered users.