Authors : Saidur Rahman, Sahil Kumar, Dr M.Sujitha, P.Sudarsan
DOI : 10.46335/IJIES.2025.10.8.18
Abstract – Spoofing detection has become a crucial and essential application for verifying security breaches. The Face Anti-Spoofing issue has made significant progress in recent years. This research addresses the problem of detecting spoofing images from unknown sources using deep learning algorithms. Specifically, we employ a combination of algorithms, including the LSTM Face matching algorithm, to differentiate between real and fake images. Our approach utilizes deep-learning techniques to detect whether a human face is genuine or spoofed. We implement CNN-based algorithms and deep learning models for image visualization and recognition of real and fake images. This paper explores the application of these advanced techniques in the context of face anti-spoofing, aiming to enhance security measures and improve the accuracy of facial recognition systems [1]-[3].
