FASS: Face Anti-Spoofing System Using Image Quality Features and Deep Learning

Face Spoofing Detection Using Image Distortion Features

Accurate biometric system for authentication is the need of the hour in today’s scenario. In face spoofing attack a person tries to pretend to be a valid user by using photo or video of an authorized person and gets illegitimate access. Hence it is essential to develop a robust and authentic face spoof detection system in order to protect the privacy about the person. Centre of attraction of th...

Anti-spoofing, Face

Integration of image quality and motion cues for face anti-spoofing: A neural network approach

Many trait-specific countermeasures to face spoofing attacks have been developed for security of face authentication. However, there is no superior face anti-spoofing technique to deal with every kind of spoofing attack in varying scenarios. In order to improve the generalization ability of face anti-spoofing approaches, an extendable multi-cues integration framework for face anti-spoofing usin...

Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision

Face anti-spoofing is crucial to prevent face recognition systems from a security breach. Previous deep learning approaches formulate face anti-spoofing as a binary classification problem. Many of them struggle to grasp adequate spoofing cues and generalize poorly. In this paper, we argue the importance of auxiliary supervision to guide the learning toward discriminative and generalizable cues....

Improving Face Image Extraction by Using Deep Learning Technique

The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-i multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces (“face images”). Some of these face images are acquired in unconstrained settings, while others are studio ...