ANDROID-BASED FACE-DETECTION, ENROLMENT AND VERIFICATIONANDROID-BASED FACE-DETECTION, ENROLMENT AND VERIFICATION
Abstract
The increasing reliançe on biometric technologies has amplified the demand for systems that can ensure both secure and efficient authentication processes. This project focuses on the design and implementation of an Android-based face identification, enrollment, and verification system. The system leverages advanced face recognition algorithms, particularly Convolutional Neural Networks (CNNs), to ensure accuracy and reliability Using real-world datasets and advanced recognition models like FaceNet and LBP, the system achieves high recognition accuracy. It is particularly suited for mobile environments, addressing challenges like variations in lighting, angles, and real-time processing constraints. By combining state-of-the-art technologies with practical application scenarios, this system demonstrates the potential of Android devices as a platform for robust biometric authentication. The system is alidated through rigorous testing, yielding encouraging results in terms of accuracy and user satisfaction.
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