Texture, Quality, and Motion-Based Analysis for Face Spoofing Detection System: A Review
Neetika Gupta, Amandeep Kaur · 2023
Face recognition systems' use, credibility, and implementation are rapidly increasing due to their efficient and non-intrusive advantages over other biometric systems, such as speech recognition and identification. However, it also faces a significant vulnerability: face spoofing attacks, which can occur when a person's photos or videos are easily obtained from the internet or captured without their consent or physical presence. Thus, there is a growing need for the development of face spoofing detection methods. Researchers have proposed various ways in this field, but a reliable face spoofing solution is essential for a robust face biometric system. This study conducts a comprehensive review of the literature on face spoofing and presents the various methods that have been planned. This survey paper covers different ways of face spoof recognition and types of face spoof attacks and categorizes the various face spoofing techniques. Despite the advancements in this field, finding a computationally effective solution remains challenging. This survey article also explains the distinct categories of face spoof attacks, such as 2D and 3D attacks, further divided into photo, video, and mask attacks. Additionally, the paper describes various feature extraction techniques, such as the LBP, grey level co-occurrence matrix, histogram of oriented optical flows, binarized statistical image, and classification methods, such as KNN, and SVM, for face spoofing detection.